Systems, devices, and methods for detection of malaria

ABSTRACT

Systems, devices, and methods are described for providing a monitor or treatment device configured to, for example, detect hemozoin, as well as to monitor or treat a malarial infection.

CROSS-REFERENCE TO RELATED APPLICATIONS

All subject matter of the Related Applications and of any and allparent, grandparent, great-grandparent, etc. applications of the RelatedApplications is incorporated herein by reference to the extent suchsubject matter is not inconsistent herewith.

RELATED APPLICATIONS

For purposes of the USPTO extra-statutory requirements, the presentapplication constitutes a continuation-in-part of U.S. patentapplication Ser. No. 12/658,619, titled SYSTEMS, DEVICES, AND METHODSINCLUDING MULTI-HARMONIC OPTICAL DETECTION OF HEMOZOIN NANOPARTICLES,naming MICHAEL C. HEGG, MATTHEW P. HORNING, JORDIN T. KARE, NATHAN P.MYHRVOLD, CLARENCE T. TEGREENE, BENJAMIN K. WILSON, LOWELL L. WOOD, JR.as inventors, filed 10 Feb. 2010, which is currently co-pending or is anapplication of which a currently co-pending application is entitled tothe benefit of the filing date.

For purposes of the USPTO extra-statutory requirements, the presentapplication constitutes a continuation-in-part of U.S. patentapplication Ser. No. 12/658,580, titled SYSTEMS, DEVICES, AND METHODSINCLUDING ENHANCED DARK FIELD DETECTION OF HEMOZOIN NANOPARTICLES,naming MICHAEL C. HEGG, MATTHEW P. HORNING, JORDIN T. KARE, NATHAN P.MYHRVOLD, CLARENCE T. TEGREENE, BENJAMIN K. WILSON, LOWELL L. WOOD, JR.as inventors, filed 10 Feb. 2010, which is currently co-pending or is anapplication of which a currently co-pending application is entitled tothe benefit of the filing date.

For purposes of the USPTO extra-statutory requirements, the presentapplication constitutes a continuation-in-part of U.S. patentapplication Ser. No. 12/658,617, titled SYSTEMS, DEVICES, AND METHODSINCLUDING VARYING A MAGNETIC FIELD TO HEAT-SHOCK MALARIA INFECTEDERYTHROCYTES, naming MICHAEL C. HEGG, MATTHEW P. HORNING, JORDIN T.KARE, NATHAN P. MYHRVOLD, CLARENCE T. TEGREENE, BENJAMIN K. WILSON,LOWELL L. WOOD, JR. as inventors, filed 10 Feb. 2010, which is currentlyco-pending or is an application of which a currently co-pendingapplication is entitled to the benefit of the filing date.

For purposes of the USPTO extra-statutory requirements, the presentapplication constitutes a continuation-in-part of U.S. patentapplication Ser. No. 12/658,638, titled SYSTEMS, DEVICES, AND METHODSINCLUDING PARAMAGNETIC OSCILLATION, ROTATION AND TRANSLATION OF HEMOZOINASYMMETRIC NANOPARTICLES IN RESPONSE TO MULTI-HARMONIC OPTICAL DETECTIONOF THE PRESENCE OF HEMOZOIN, naming MICHAEL C. HEGG, MATTHEW P. HORNING,JORDIN T. KARE, NATHAN P. MYHRVOLD, CLARENCE T. TEGREENE, BENJAMIN K.WILSON, LOWELL L. WOOD, JR. as inventors, filed 10 Feb. 2010, which iscurrently co-pending or is an application of which a currentlyco-pending application is entitled to the benefit of the filing date.

For purposes of the USPTO extra-statutory requirements, the presentapplication constitutes a continuation-in-part of U.S. patentapplication Ser. No. 12/658,589, titled SYSTEMS, DEVICES, AND METHODSINCLUDING PARAMAGNETIC OSCILLATION, ROTATION, AND TRANSLATION OFHEMOZOIN ASYMMETRIC NANOPARTICLES IN RESPONSE TO DARK-FIELD OR RHEINBERGDETECTION OF THE PRESENCE OF HEMOZOIN, naming MICHAEL C. HEGG, MATTHEWP. HORNING, JORDIN T. KARE, NATHAN P. MYHRVOLD, CLARENCE T. TEGREENE,BENJAMIN K. WILSON, LOWELL L. WOOD, JR. as inventors, filed 10 Feb.2010, which is currently co-pending or is an application of which acurrently co-pending application is entitled to the benefit of thefiling date.

For purposes of the USPTO extra-statutory requirements, the presentapplication constitutes a continuation-in-part of U.S. patentapplication Ser. No. 12/658,607, titled SYSTEMS, DEVICES, AND METHODSFOR INDUCING ULTRAVIOLET ENERGY GENERATION VIA HEMOZOIN NANOPARTICLES INA BIOLOGICAL TISSUE, naming MICHAEL C. HEGG, MATTHEW P. HORNING, JORDINT. KARE, NATHAN P. MYHRVOLD, CLARENCE T. TEGREENE, BENJAMIN K. WILSON,LOWELL L. WOOD, JR. as inventors, filed 10 Feb. 2010, which is currentlyco-pending or is an application of which a currently co-pendingapplication is entitled to the benefit of the filing date.

The USPTO has published a notice to the effect that the USPTO's computerprograms require that patent applicants reference both a serial numberand indicate whether an application is a continuation orcontinuation-in-part. Stephen G. Kunin, Benefit of Prior-FiledApplication, USPTO Official Gazette Mar. 18, 2003, available athttp://www.uspto.gov/web/offices/com/sol/og/2003/week11/patbene.htm. Thepresent Applicant Entity (hereinafter “Applicant”) has provided above aspecific reference to the application(s)from which priority is beingclaimed as recited by statute. Applicant understands that the statute isunambiguous in its specific reference language and does not requireeither a serial number or any characterization, such as “continuation”or “continuation-in-part,” for claiming priority to U.S. patentapplications. Notwithstanding the foregoing, Applicant understands thatthe USPTO's computer programs have certain data entry requirements, andhence Applicant is designating the present application as acontinuation-in-part of its parent applications as set forth above, butexpressly points out that such designations are not to be construed inany way as any type of commentary and/or admission as to whether or notthe present application contains any new matter in addition to thematter of its parent application(s).

All subject matter of the Related Applications and of any and allparent, grandparent, great-grandparent, etc. applications of the RelatedApplications is incorporated herein by reference to the extent suchsubject matter is not inconsistent herewith.

SUMMARY

In an aspect, the present disclosure is directed to, among other things,a dark-field reflected-illumination apparatus. In an embodiment, thedark-field reflected-illumination apparatus includes a dark-fieldilluminator and means for adjusting a dark-field illuminator distancerelative to an optical assembly. In an embodiment, the dark-fieldilluminator includes a body structure having an aperture and a pluralityof waveguide assemblies. In an embodiment, the plurality of waveguideassemblies include one or more electromagnetic energy waveguidesconfigured to be coupled to at least one electromagnetic energy emitter.In an embodiment, the plurality of waveguide assemblies are oriented tofocus electromagnetic energy onto at least one focal region within theaperture and at one or more angles of incidence relative to an opticalaxis of an optical assembly.

In an aspect, the present disclosure is directed to, among other things,malaria detection apparatus. In an embodiment, the malaria detectionapparatus includes an optical assembly having a sample side, a detectorside, and an optical axis therethrough. In an embodiment, the malariadetection apparatus includes a dark-field illuminator and a detector. Inan embodiment, the malaria detection apparatus includes means foradjusting a dark-field illuminator distance relative to the opticalassembly along an axis substantially parallel to an optical axis of theoptical assembly. In an embodiment, the dark-field illuminator includesa plurality of waveguide assemblies, and a body structure having anaperture aligned along an axis substantially parallel to an opticalaxis. In an embodiment, the optical assembly is configured to receivescattered electromagnetic energy from a sample interrogated by thedark-field illuminator. In an embodiment, the detector includes one ormore sensor 442 that capture one or more micrographs associated with thescattered electromagnetic energy from the sample interrogated by thedark-field illuminator.

In an aspect, the present disclosure is directed to, among other things,a system. In an embodiment, the system includes a detection circuitconfigured to acquire one or more micrographs of a biological sample atone or more fields of view. In an embodiment, the system includes aresolution modification circuit configured to modify a pixel count of atleast one micrograph and to generate at least a first modifiedmicrograph. In an embodiment, the system includes a filter-kernelgeneration circuit configured to generate a kernel for filtering aplurality of pixels forming the first modified micrograph based on afiltering characteristic, and to generate at least a first significanceimage representative of the at least one modified micrograph. In anembodiment, the system includes an object identification circuitconfigured to identify groups of pixels in the first significance imageindicative of one or more objects imaged in the at least one micrograph,and to generate one or more connected components of a graphrepresentative of groups of pixels indicative of the one or more objectsimaged in the at least one micrograph.

In an aspect, the present disclosure is directed to, among other things,a method including acquiring, using a detection circuit, one or moremicrographs of a biological sample at one or more fields of view. In anembodiment, the method includes modifying a resolution of at least oneof the one or more micrographs and generating at least a first modifiedmicrograph. In an embodiment, the method includes generating a firstfiltered micrograph by filtering the at least first modified micrographbased on a filtering protocol. In an embodiment, the method includesdetermining a disease state by identifying objects of the biologicalsample in the filtered micrograph.

The foregoing summary is illustrative only and is not intended to be inany way limiting. In addition to the illustrative aspects, embodiments,and features described above, further aspects, embodiments, and featureswill become apparent by reference to the drawings and the followingdetailed description.

BRIEF DESCRIPTION OF THE FIGURES

FIG. 1A is a perspective view of a system according to one embodiment.

FIG. 1B is a top plan view of a portion of a monitor or treatment deviceincluding at least one energy emitting component delivering a patternedelectromagnetic energy stimulus, according to one embodiment.

FIG. 2A is a perspective view of a system for modulating plasmodiumparasitic activity according to one embodiment.

FIG. 2B is a perspective view of a system for monitoring/modulating aplasmodium parasitic activity according to one embodiment.

FIG. 3A is a perspective view of a hemozoin-monitoring device accordingto one embodiment.

FIG. 3B is a perspective view of a medical diagnostic device accordingto one embodiment.

FIG. 3C is a perspective view of a medical diagnostic device accordingto one embodiment.

FIG. 3D is a perspective view of an in situ hemozoin-monitoring deviceaccording to one embodiment.

FIG. 3E is a perspective view of an anti-malarial therapeutic deviceaccording to one embodiment.

FIG. 4A is a perspective view of an apparatus according to oneembodiment.

FIG. 4B is a perspective view of an apparatus according to oneembodiment.

FIG. 5 is a flow diagram of a method according to one embodiment.

FIG. 6 is a flow diagram of a method according to one embodiment.

FIG. 7 is a flow diagram of a method according to one embodiment.

FIG. 8 is a flow diagram of a method according to one embodiment.

FIG. 9 is a flow diagram of a method according to one embodiment.

FIG. 10 is a flow diagram of a method according to one embodiment.

FIG. 11 is a flow diagram of a method according to one embodiment.

FIG. 12 is a flow diagram of a method according to one embodiment.

FIG. 13 is a flow diagram of a method according to one embodiment.

FIG. 14 is a flow diagram of a method according to one embodiment.

FIG. 15 is a flow diagram of a method according to one embodiment.

FIG. 16 is a flow diagram of a method according to one embodiment.

FIG. 17 is a flow diagram of a method according to one embodiment.

FIGS. 18A and 18B show a flow diagram of a method according to oneembodiment.

FIG. 19 is a flow diagram of a method according to one embodiment.

FIG. 20 is a perspective view of a monitor or treatment deviceconfiguration according to one embodiment.

FIGS. 21A and 21B show top plan views of respective representativez-scan and lateral scans methodologies from hemozoin thin-filmsaccording to one embodiment.

FIG. 22 Third Harmonic Generation (THG) Intensity vs. Lateral Distanceplot of (1) hemozoin and (2) quartz according to one embodiment.

FIGS. 23A and 23B show Third Harmonic Generation (THG) Power vs.Excitation Power plots according to multiple illustrated embodiments.

FIG. 24 is a Photo Multiplier Tube (PMT) current vs. Power Fraction plotaccording to one embodiment.

FIG. 25 is a voxel image of hemozoin crystals in infected red bloodcells according to one embodiment.

FIG. 26 is a two-dimensional spatial scan of infected and uninfectederythrocytes showing intensity peaks that correspond to hemozoincrystals in the infected cells, according to one embodiment.

FIG. 27 is a Photo Multiplier Tube (PMT) current vs. Time plot accordingto one embodiment.

FIG. 28 is a Third Harmonic Generation (THG) vs. Signal Power plotaccording to one embodiment.

FIG. 29 is a Third Harmonic Generation (THG) vs. Time plot according toone embodiment.

FIG. 30 is a Detected Wavelength vs. Source Wavelength plot according toone embodiment.

FIG. 31A is a prospective view of a monitor or treatment deviceaccording to one embodiment.

FIG. 31B is a prospective view of a monitor or treatment device usingepi-detection according to one embodiment.

FIG. 32A is a prospective view of a monitor or treatment device usingThird Harmonic Generation (THG) detection according to one embodiment.

FIG. 32B is a prospective view of a monitor or treatment device usingDark-field detection according to one embodiment.

FIG. 33 is an exploded view of a monitor or treatment device usingDark-field detection according to one embodiment.

FIG. 34 is an exploded view of a Dark-field illuminator according to oneembodiment.

FIG. 35 is cross-sectional view of a monitor or treatment device usingDark-field detection according to one embodiment.

FIG. 36 is a perspective view of a system according to one embodiment.

FIGS. 37A and 37B show a flow diagram of a method according to oneembodiment.

FIG. 38 is a schematic view of a system according to an embodiment.

DETAILED DESCRIPTION

In the following detailed description, reference is made to theaccompanying drawings, which form a part hereof. In the drawings,similar symbols typically identify similar components, unless contextdictates otherwise. The illustrative embodiments described in thedetailed description, drawings, and claims are not meant to be limiting.Other embodiments may be utilized, and other changes may be made,without departing from the spirit or scope of the subject matterpresented here.

An aspect of the disclosure includes systems, devices, and methods fordetecting (e.g., assessing, calculating, evaluating, determining,gauging, identifying, measuring, monitoring, quantifying, resolving,sensing, or the like) an agent marker present in, for example, abiological sample (e.g., blood, bone, muscle, skin, adipose tissue,fluid, tendons, organs, ventricles, or the like, either in vivo or invitro). Agent markers can include markers indicating the presence of aninfectious agent, for example. A non-limiting example includes systems,devices, and methods of actively monitoring a biological subjectsuspected of being infected with a plasmodium parasite. A non-limitingexample includes systems, devices, and methods including dark-field orRheinberg detection technologies and methodologies.

Malaria remains one of the most important communicable diseases in theworld. The World Health Organization estimates that about half of theworld's population lives in areas having some risk of exposure tomalaria. See, e.g., World Health Organization, World Malaria Report2008, WHO: Geneva 9 (2008). Malaria is a vector-borne infectious diseasecaused by a eukaryotic protist of the genus Plasmodium. Among Plasmodiumspecies that can infect humans, examples include Plasmodium falciparum,Plasmodium knowlesi, Plasmodium malariae, Plasmodium ovale, andPlasmodium vivax. A 2006 World Health Organization estimate indicatesthat about 247 million cases of malaria occur annually of which 230million are due to Plasmodium falciparum. See, e.g., World HealthOrganization, World Malaria Report 2008, WHO: Geneva 10 (2008).

The protozoan Plasmodium parasite, the agent of malaria, produceshemozoin (a birefringent heme crystal) while inside the hemoglobin-ladenerythrocyte. See e.g., Lamikanra et al, Hemozoin (Malarial Pigment)Directly Promotes Apoptosis of Erythroid Precursors. PLoS ONE 4(12)(2009): e8446. doi:10.1371/journal.pone.0008446. Hemozoin, a biomarkerfor malaria, is synthesized during the degradation of hemoglobin and isfound in the digestive food vacuole of intraerythrocytic Plasmodiumparasites.

An aspect of the disclosure includes systems, devices, and methodsincluding multi-harmonic optical detection of hemozoin nanoparticles. Anon-limiting example includes systems, devices, and methods includingenhanced dark field detection of hemozoin nanoparticles. An aspect ofthe disclosure includes systems, devices, methods, and compositions foractively detecting and treating a malarial infection. A non-limitingexample includes systems, devices, and methods for heat-shocking malariainfected erythrocytes. A non-limiting example includes systems, devices,and methods including paramagnetic oscillation, rotation, andtranslation of hemozoin asymmetric nanoparticles in response tomulti-harmonic optical detection of the presence of hemozoin. Anon-limiting example includes systems, devices, and methods includingultraviolet energy generation via hemozoin nanoparticles in a biologicaltissue.

FIG. 1A shows a system 100, in which one or more methodologies ortechnologies can be implemented such as, for example, actively detectingor treating a malarial infection. In an embodiment, the system 100includes, among other things, one or more monitor or treatment devices102. Nonlimiting examples of monitor or treatment devices 102 includehemozoin-monitoring devices, spectrometers, anti-malarial therapeuticdevices, malarial retinal diagnostic devices, transcutaneous diagnosticdevices 102 a, ophthalmoscopes 102 b (e.g., ophthalmoscopes employingnonlinear optics, dark-field, or Rheinberg detection configurations,technologies, and methodologies), parasitemia detectors, malariadetection apparatuses 102 c, or the like.

In an embodiment, the system 100 includes, among other things, anenergy-emitting component 104 configured to interrogate one or morefocal volumes with an electromagnetic energy stimulus. Non-limitingexamples of energy-emitting components 104 include electromagneticradiation emitters, electric circuits, electrical conductors, cavityresonators, electro-mechanical components, electro-opto components,lasers, quantum dots, laser diodes, light-emitting diodes (e.g., organiclight-emitting diodes, polymer light-emitting diodes, polymerphosphorescent light-emitting diodes, microcavity light-emitting diodes,high-efficiency light-emitting diodes, or the like), arc flashlamps,incandescent emitters, continuous wave bulbs, or the like. In anembodiment, the energy-emitting component 104 includes at least onetwo-photon excitation component. In an embodiment, the energy-emittingcomponent 104 includes one or more lasers, laser diodes, andlight-emitting diodes. In an embodiment, the energy-emitting component104 includes one or more quantum dots, organic light-emitting diodes,microcavity light-emitting diodes, and polymer light-emitting diodes. Inan embodiment, the energy-emitting component 104 includes at least oneof an exciplex laser, a diode-pumped solid state laser, or asemiconductor laser. In an embodiment, the energy-emitting component 104includes one or more tunable ultrafast lasers. In an embodiment, theenergy-emitting component 104 includes one or more femtosecond lasers.In an embodiment, the energy-emitting component 104 includes one or moreTi:sapphire lasers. In an embodiment, the energy-emitting component 104interrogates at least one focal volume with a spatially-patternedelectromagnetic energy stimulus having at least a first region and asecond region different from the first region. In an embodiment, theenergy-emitting component 104 interrogates at least one focal volumewith a spatially-patterned electromagnetic energy stimulus having atleast a first region and a second region, the second region having atleast one of an illumination intensity, an energy-emitting pattern, apeak emission wavelength, an ON-pulse duration, an OFF-pulse duration,or a pulse frequency different from the first region. In an embodiment,the energy-emitting component 104 interrogates at least one focal volumewith a spatially-patterned pulsed multiplexed electromagnetic energystimulus. In an embodiment, the energy-emitting component 104 generatesa multiplexed electromagnetic energy stimulus having, for example, twoor more peak emission wavelengths.

In an embodiment, the electromagnetic energy-emitting component 104 isconfigured to direct (e.g., via one or more waveguides) electromagneticradiation toward a biological sample (e.g., tissue, blood capillariesunderneath the skin, or the like). If the biological sample is infectedwith malaria parasites, the hemozoin within them will emit acharacteristic optical response back through the skin.

In an embodiment, by adjusting the wavelength of the electromagneticstimulus generated by the energy emitting component 104, it is possibleto control the wavelength of light that emerges from the hemozoin (i.e.,it is possible to control the wavelength of the emerging nonlinearoptical response of the hemozoin. In an embodiment, one or more peakemission wavelengths of the electromagnetic stimulus generated by theenergy-emitting component 104 are chosen to elicit a nonlinear opticalresponse of hemozoin to emit within a wavelength range that damagesgenetic material.

In an embodiment, the energy-emitting component 104 delivers aspatially-patterned pulsed multiplexed electromagnetic energy stimulushaving a peak power ranging from about 400 gigawatts to about 8terawatts. In an embodiment, the energy-emitting component 104 generatesa spatially-patterned pulsed multiplexed electromagnetic energy stimulushaving a peak irradiance of less than about 200 gigawatts/cm̂2. In anembodiment, the energy-emitting component 104 generates aspatially-patterned pulsed multiplexed electromagnetic energy stimulushaving an average power ranging from about 1 miliwatt to about 1 watt.In an embodiment, the energy-emitting component 104 generates aspatially-patterned pulsed multiplexed electromagnetic energy stimulushaving one or more peak emission wavelengths ranging from about 690nanometers to about 2000 nanometers. In an embodiment, theenergy-emitting component 104 generates spatially-patterned pulsedmultiplexed electromagnetic energy stimulus having a resolution[0.61*(peak emission wavelength/numerical aperture)] ranging from about300 nanometers to about 10 micrometers. Energy-emitting components 104forming part of a monitor or treatment device 102, can take a variety offorms, configurations, and geometrical patterns including for example,but not limited to, a one-, two-, or three-dimensional arrays, a patterncomprising concentric geometrical shapes, a pattern comprisingrectangles, squares, circles, triangles, polygons, any regular orirregular shapes, or the like, or any combination thereof. One or moreof the energy-emitting components 104 may have a peak emissionwavelength in the x-ray, ultraviolet, visible, infrared, near infrared,terahertz, microwave, or radio frequency spectrum. In an embodiment, theenergy-emitting component 104 includes a patterned energy-emittingsource. In an embodiment, the energy-emitting component 104 includes apatterned light-emitting source.

In an embodiment, the energy-emitting component 104 concurrently orsequentially interrogates multiple focal volumes with thespatially-patterned pulsed multiplexed electromagnetic energy stimulus.In an embodiment, the energy-emitting component 104 concurrently orsequentially interrogates multiple focal volumes with aspatially-patterned, multifocal depth, electromagnetic energy stimulus.

In an embodiment, the energy-emitting component 104 delivers anelectromagnetic energy stimulus having at least a first peak emissionwavelength and a second peak emission wavelength different from thefirst peak emission wavelength. In an embodiment, the energy-emittingcomponent 104 includes at least one of a first energy emitter and atleast one of a second energy emitter, the at least one second energyemitter having a peak emission wavelength different from the at leastone first energy emitter. In an embodiment, the energy-emittingcomponent 104 concurrently or sequentially delivers a first pulsedelectromagnetic energy stimulus and a second pulse electromagneticenergy stimulus, the second pulsed energy stimulus having at least oneof a pulse duration, a pulse frequency, a pulse intensity, a pulseratio, or a pulse repetition rate different from the first pulsedelectromagnetic energy stimulus. In an embodiment, the energy-emittingcomponent 104 concurrently or sequentially delivers a first pulsedelectromagnetic energy stimulus and a second pulse electromagneticenergy stimulus, the second pulsed electromagnetic energy stimulushaving a focal depth different from the first pulsed electromagneticenergy stimulus. In an embodiment, the energy-emitting component 104concurrently or sequentially delivers a first pulsed electromagneticenergy stimulus and a second pulse electromagnetic energy stimulus, thesecond pulsed electromagnetic energy stimulus having a resolutiondifferent from the first pulsed electromagnetic energy stimulus. In anembodiment, at least a portion of the energy-emitting component 104 isconfigured for removable attachment to a biological surface of abiological subject.

In an embodiment, the energy-emitting component 104 is configured todeliver a spatially-focused electromagnetic energy stimulus.

In an embodiment, the energy-emitting component 104 includes a lensarray configured to deliver a spaced-apart energy stimuli having atleast a first region and at least a second region, the second regionhaving a focal depth different from the first region. In an embodiment,the second region has a peak emission wavelength different from thefirst region. In an embodiment, the second region has a peak irradiancedifferent from the first region. In an embodiment, the second region hasat least one of an intensity, frequency, pulse intensity, pulseduration, pulse ratio, and pulse repetition rate different from anintensity, frequency, pulse intensity, pulse duration, pulse ratio, andpulse repetition rate of the first region. In an embodiment, theenergy-emitting component 104 includes one or more orthogonal (orcrossed) polarizers. In an embodiment, the sensor component 440 includesone or more orthogonal (or crossed) polarizers.

In an embodiment, the energy-emitting component 104 includes a pluralityof selectively-actuatable electromagnetic energy waveguides that directan emitted spatially-patterned pulsed multiplexed electromagnetic energystimulus to one or more regions of the at least one focal volume. In anembodiment, the energy-emitting component 104 includes a dark-fieldelectromagnetic energy emitting component to deliver a multi-modedark-field interrogation stimulus to at least one blood vessel.

Referring to FIG. 1B, in an embodiment, the energy-emitting component104 provides an illumination pattern 600 comprising at least a firstregion 202 and a second region 204. In an embodiment, the second region204 of the illumination pattern 600 comprises at least one of anillumination intensity (I_(n)), an energy-emitting pattern, a peakemission wavelength (λ_(n)), an ON-pulse duration (D_((ON))), anOFF-pulse duration (D_((OFF))), or a pulse frequency (ν_(n)) differentfrom the first region 202. The energy-emitting component 104 can beconfigured to provide a spatially patterned electromagnetic energystimulus having a peak emission wavelength in at least one of an x-ray,an ultraviolet, a visible, an infrared, a near infrared, a terahertz,microwave, or a radio frequency spectrum, or combinations thereof, to atleast a portion of tissue proximate an monitor or treatment device 102.In an embodiment, the energy-emitting component 104 provides a spatiallypatterned optical energy stimulus. In an embodiment, the monitor ortreatment device 102 includes, among other things, a patterned-lightemitting source. In an embodiment, the patterned-light emitting sourceprovides a spatially patterned energy stimulus to one or more region ofa biological subject.

With continued reference to FIG. 1A, in an embodiment, the system 100includes, among other things, circuitry 108 configured to detect (e.g.,assess, calculate, evaluate, determine, gauge, measure, monitor,quantify, resolve, sense, or the like) a nonlinear optical response(e.g., a nonlinear multi-harmonic response, nonlinear multi-harmonicresponse energy associated with hemozoin nanoparticles within the atleast one focal volume interrogated by an electromagnetic energystimulus, or the like). In an embodiment, circuitry includes one or morecomponents operably coupled (e.g., communicatively coupled,electromagnetically, magnetically, ultrasonically, optically,inductively, electrically, capacitively coupleable, or the like) to eachother. In an embodiment, circuitry includes one or more remotely locatedcomponents. In an embodiment, remotely located components can beoperably coupled via wireless communication. In an embodiment, remotelylocated components can be operably coupled via one or more receivers,transmitters, transceivers, or the like.

In an embodiment, circuitry includes, among other things, one or morecomputing devices 402 such as a processor (e.g., a microprocessor) 404,a central processing unit (CPU) 406, a digital signal processor (DSP)408, an application-specific integrated circuit (ASIC) 410, a fieldprogrammable gate array (FPGA) 412, or the like, or any combinationsthereof, and may include discrete digital or analog circuit elements orelectronics, or combinations thereof. In an embodiment, circuitryincludes, among other things, one or more field programmable gate arrays412 having a plurality of programmable logic components. In anembodiment, circuitry includes, among other things, one or more of anapplication specific integrated circuits having a plurality ofpredefined logic components. In an embodiment, at least one computingdevice 402 is operably coupled to one or energy-emitting components 104.In an embodiment, circuitry includes one or more computing devices 402configured to concurrently or sequentially operate multipleenergy-emitting components 104. In an embodiment, one or more computingdevices 402 are configured to automatically control at least onewaveform characteristic (e.g., intensity, frequency, pulse intensity,pulse duration, pulse ratio, pulse repetition rate, or the like)associated with the delivery of one or more energy stimuli. For example,pulsed waves may be characterized by the fraction of time the energystimulus is present over one pulse period. This fraction is called theduty cycle and is calculated by dividing the pulse time ON by the totaltime of a pulse period (e.g., time ON plus time OFF). In an embodiment,a pulse generator 403 may be configured to electronically generatepulsed periods and non-pulsed (or inactive) periods. In an embodiment,circuitry includes a computing device 402 operably coupled to theenergy-emitting component 104, the computing device configured tocontrol at least one parameter associated with a delivery of thespatially-patterned pulsed multiplexed electromagnetic energy stimulus.

In an embodiment, the computing device 402 is configured to control atleast one of a delivery regimen, a spaced-apart delivery pattern, aspatial modulation, a temporal modulation, a magnitude, aspatial-pattern configuration, or a spatial distribution associated withthe delivery of the spatially-patterned multiplexed electromagneticenergy stimulus. In an embodiment, the computing device 402 includes oneor more processors 404 configured to control one or more parameterassociated with one or more of a spatial illumination modulation, aspatial illumination intensity, or a spatial illumination deliverypattern associated with a delivery of the spatially-patterned pulsedmultiplexed electromagnetic energy stimulus. In an embodiment, thecomputing device 402 includes one or more processors 404 configured tocontrol one or more parameters associated a pulse frequency, a pulseintensity, a pulse ratio, or a pulse repetition rate associated with adelivery of the spatially-patterned pulsed multiplexed electromagneticenergy stimulus. In an embodiment, the computing device 402 includes oneor more processors 404 configured to control one or more parametersassociated a focal depth distribution associated with a delivery of thespatially-patterned pulsed multiplexed electromagnetic energy stimulus.In an embodiment, the computing device 402 includes one or moreprocessors 404 operably coupled to the energy-emitting component andconfigured to control a spatial distribution of the spatially-patternedpulsed multiplexed electromagnetic energy stimulus. In an embodiment,the system 100 includes at least one processor 404 operable to cause astoring of information associated with magnetically inducing at leastone of an oscillation, translation, and rotation of hemozoinnanoparticles in a biological tissue. In an embodiment, the system 100at least one processor 404 operable to cause a storing of informationassociated with comparing a nonlinear multi-harmonic responseinformation to reference hemozoin response information on one or morecomputer-readable storage media.

In an embodiment, the computing device 402 includes one or moreprocessors 404 for generating a control signal associated with activelycontrolling at least one of a duty cycle, a pulse train frequency, andpulse repetition rate associated with a magnetic field applied to thebiological sample. In an embodiment, the computing device 402 includesone or more processors 404 for generating a control signal associatedwith actively controlling a magnetic field orientation. In anembodiment, the computing device 402 includes one or more processors 404for generating a control signal associated with actively controlling amagnetic field strength. In an embodiment, the computing device 402includes one or more processors 404 for generating a control signalassociated with actively controlling a magnetic field spatialdistribution. In an embodiment, the computing device 402 includes one ormore processors 404 for generating a control signal associated withactively controlling a magnetic field temporal pattern. In anembodiment, the computing device 402 includes one or more processors 404for generating a control signal associated with actively controlling amagnetic field ON duration. In an embodiment, the computing device 402includes one or more processors 404 for generating a control signalassociated with actively controlling a polarization of a generatedmagnetic field.

In an embodiment, the computing device 402 is configured to actuate theactively-controllable magnetic field generator in response to acomparison of a detected nonlinear multi-harmonic response profile toone or more reference hemozoin nonlinear response profiles. In anembodiment, the computing device 402 is configured to change at leastone of a magnetic field ON duration, a magnetic field strength, amagnetic field frequency, or a magnetic field in response to thesensor's detection of a nonlinear multi-harmonic response profileassociated with hemozoin nanoparticles in the biological sample. In anembodiment, the computing device 402 is configured to change a magneticfield spatial distribution pattern in response to the sensor's detectionof a nonlinear multi-harmonic response profile associated with hemozoinnanoparticles in the biological sample. In an embodiment, the computingdevice 402 is configured to change a magnetic field temporal pattern inresponse to the sensor's detection of a nonlinear multi-harmonicresponse profile associated with hemozoin nanoparticles in thebiological sample.

In an embodiment, circuitry includes, among other things, one or morememories 414 that, for example, store instructions or data, for example,volatile memory (e.g., Random Access Memory (RAM) 416, Dynamic RandomAccess Memory (DRAM), or the like), non-volatile memory (e.g., Read-OnlyMemory (ROM) 418, Electrically Erasable Programmable Read-Only Memory(EEPROM), Compact Disc Read-Only Memory (CD-ROM), or the like),persistent memory, or the like. Further non-limiting examples of one ormore memories 414 include Erasable Programmable Read-Only Memory(EPROM), flash memory, or the like. The one or more memories 414 can becoupled to, for example, one or more computing devices 402 by one ormore instruction, data, or power buses 420.

In an embodiment, circuitry includes, among other things, one or moredatabases 422. In an embodiment, a database 422 includes at least one ofreference hemozoin spectral response information, reference hemozoinnonlinear optical response information, heuristically determinedparameters associated with at least one in vivo or in vitro determinedmetric. In an embodiment, a database 422 includes at least one ofabsorption coefficient data, extinction coefficient data, scatteringcoefficient data, or the like. In an embodiment, a database 422 includesat least one of stored reference data such as infectious agent markerdata, or the like. In an embodiment, a database 422 includes referenceobject information. In an embodiment, a database 422 includes at leastone of erythrocyte graph information, malaria-infected erythrocyte graphinformation, or hemozoin graph information.

In an embodiment, a database 422 includes information associated with adisease state of a biological subject. In an embodiment, a database 422includes measurement data. In an embodiment, a database 422 includes atleast one of cryptographic protocol information, regulatory complianceprotocol information (e.g., FDA regulatory compliance protocolinformation, or the like), regulatory use protocol information,authentication protocol information, authorization protocol information,delivery regimen protocol information, activation protocol information,encryption protocol information, decryption protocol information,treatment protocol information, or the like. In an embodiment, adatabase 422 includes at least one of electromagnetic energy stimuluscontrol delivery information, electromagnetic energy emitter controlinformation, power control information, or the like.

In an embodiment, the system 100 is configured to compare an inputassociated with at least one characteristic associated with a biologicalsubject to a database 422 of stored reference values, and to generate aresponse based in part on the comparison. In an embodiment, the system100 is configured to compare an input associated with at least onecharacteristic associated the presence of hemozoin to a database 422 ofstored reference values, and to generate a response based in part on thecomparison.

In an embodiment, the system 100 includes, among other things, circuitry108 configured to detect a nonlinear multi-harmonic spectral responseresulting from interrogating a biological sample suspected of havinghemozoin with an electromagnetic energy stimulus.

The behavior of electric fields, magnetic fields, charge density, andcurrent density can be described, for example, by Maxwell's equations.See Saleh et al., Fundamentals of Photonics, pp. 152-170 (2^(nd)Edition; 2007). Nonlinear optical phenomena include, among other things,those interactions of electromagnetic radiation with matter where theresponse of the matter (e.g., polarization, power absorption, or thelike) is not linearly proportional (i.e., the amount of the responsedoes not scale linearly) to the variables describing the electromagneticradiation (e.g., irradiance, electric field strength, energy flux,fundamental wavelength, fundamental frequency, or the like). In anembodiment, the energy-emitting component 104 delivers anelectromagnetic energy stimulus to one or more focal volumes suspectedof containing hemozoin. Depending on the character and duration of theelectromagnetic energy, the interaction of the electromagnetic stimuluswith hemozoin within one or more focal volumes results in the generationof a nonlinear optical response that is detected via, for example,scattered radiation.

Nonlinear optical phenomena include, among other things, second harmonicgeneration (generation of light with a doubled frequency; one-half thewavelength of a fundamental wavelength emitted by an electromagneticenergy source), third harmonic generation (generation of light with atripled frequency; one-third the wavelength of a fundamental wavelengthemitted by an electromagnetic energy source), fourth harmonicgeneration, difference frequency generation, high harmonic generation,optical parametric amplification, optical parametric generation, opticalparametric oscillation, optical rectification, spontaneous parametricdown conversion, sum frequency generation, or the like. Furthernon-limiting examples of nonlinear optical phenomena include Brillouinscattering, multiple photo-ionization, optical Kerr effect, two-photonabsorption, or the like.

The polarization density relationship describing the interaction ofelectromagnetic radiation with matter can be approximated (forsufficiently weak fields, assuming no permanent dipole moments arepresent) by the following sum of linear and nonlinear parts (see e.g.,Saleh et al., Fundamentals of Photonics, pp. 873-935 (2^(nd) Edition;2007):

P _(i)(E)=(ε₀χ_(ij) ⁽¹⁾ E _(j)+2χ_(ijk) ⁽²⁾ E _(j) E _(k)+4χ_(ijkl) ⁽³⁾E _(j) E _(k) E _(l)+ . . . )   (eq. 1)

where,

ε₀χ_(ij) ⁽¹⁾E_(j) describes the linear first order optical phenomenaincluding absorption and refraction;

2χ_(ijk) ⁽²⁾E_(j)E_(k) describes the second order nonlinear phenomenaincluding electro-optic rectification, Pockels electro-optic effect, andsecond-harmonic generation (e.g., frequency doubling); and

4χ_(ijkl) ⁽³⁾E_(j)E_(k)E_(l) describes the third order nonlinearphenomena including electric field-induced optical rectification,four-wave mixing, intensity-dependent refractive index, quadratic Kerreffect, self-focusing, and third-harmonic generation (e.g., frequencytripling).

In an embodiment, the circuitry 108 configured to detect the nonlinearmulti-harmonic response energy includes a sensor component 440 includingone or more sensors. In an embodiment, the sensor component 440 isconfigured to detect a nonlinear multi-harmonic response profileassociated with hemozoin nanoparticles interrogated by anelectromagnetic energy stimulus, and configured to compare the detectednonlinear multi-harmonic response profile to one or more referencehemozoin nonlinear response profiles. In an embodiment, the referencehemozoin response profile includes one or more heuristically determinedparameters associated with at least one in vivo or in vitro determinedmetric. In an embodiment, the one or more heuristically determinedparameters include at least one of a threshold level or a targetparameter. In an embodiment, the one or more heuristically determinedparameters include threshold information.

In an embodiment, the sensor component 440 includes an optical energysensor component configured to detect scattered optical energy from theplurality of hemozoin nanoparticles interrogated by the multi-modedark-field interrogation stimulus in the presence of the magnetic field.

In an embodiment, the sensor component 440 includes an electromagneticenergy sensor component configured to detect, via a dark-field detectionconfiguration, response energy associated with hemozoin nanoparticlesinterrogated by the multi-mode dark-field stimulus in the presence ofthe first electromagnetic energy stimulus. In an embodiment, the system100 includes, among other things, circuitry 110 configured to generateat least one of a multi-mode dark-field interrogation stimulus or amulti-mode Rheinberg interrogation stimulus.

In practice, a dark-field detection configuration includes blocking outof central electromagnetic energy rays (via, for example, a dark-fieldstop or an opaque object) along an optical axis on an objective lensassembly 114, which ordinarily pass through and around a sample.Blocking the central electromagnetic energy rays allows only thoseoblique rays originating at large angles (i.e., only light scattered bythe biological sample within the focal volume) to reach the detector. Inan embodiment, the dark-field detection configuration includes acompound microscope assembly including a condenser system enablingelectromagnetic energy rays emerging from a focal region in all azimuthsto form an inverted hollow cone of illumination having an apex centeredin the specimen plane. Dark-field illumination detection techniques canbe further enhanced in contrast and selectivity by adding polarizers(e.g., orthogonal (or crossed) polarizers, etc.) to the illuminator anddetector. Cross polarization limits detection to scattering events thatdepolarize the illumination, greatly reducing false positives andunwanted signal from healthy tissue. This is relevant for both imagingand spectroscopic, in vivo and in vitro system, devices, and methods.

In an embodiment, the sensor component 440 includes an electromagneticenergy sensor component configured to detect, via a Rheinberg detectionconfiguration, response energy associated with hemozoin nanoparticlesinterrogated by the multi-mode dark-field stimulus in the presence ofthe first electromagnetic energy stimulus. In practice, a Rheinbergdetection configuration resembles a dark-field detection configuration,but rather that using a dark-field stop, an opaque object, etc., alongan optical axis; the Rheinberg detection configuration includes aRheinberg filter of at least two different colors. In an embodiment, thecentral area, where the dark-field stop would typically reside, is onecolor (e.g., green) and the outer ring (annulus) a contrasting color(e.g., red). Unmodified light (light that does not impinge on thesample) fills the background with uniform light the color of the centralcircle, while modified light (light that impinges on the sample and isrefracted, scattered, etc.,) would have the color of the outer annulus.

In an embodiment, the electromagnetic energy sensor component includesat least one Rheinberg filter. In an embodiment, the electromagneticenergy sensor component is configured to detect scatter energyassociated with hemozoin nanoparticles interrogated by the multi-modedark-field stimulus in the presence of a first electromagnetic energystimulus or a second electromagnetic energy stimulus. In an embodiment,the electromagnetic energy sensor component includes at least onespectrometer. In an embodiment, the electromagnetic energy sensorcomponent is configured to detect a spectral response associated withhemozoin nanoparticles interrogated by the multi-mode dark-fieldstimulus in the presence of the first electromagnetic energy stimulus orthe second electromagnetic energy stimulus.

In an embodiment, the electromagnetic energy sensor component isconfigured to detect scatter energy associated with hemozoinnanoparticles interrogated by the multi-mode dark-field stimulus in thepresence of the first electromagnetic energy stimulus or the secondelectromagnetic energy stimulus.

In an embodiment, the system 100 includes, among other things, a sensorcomponent 440 including at least one sensor 442 configured to detectnonlinear multi-harmonic response energy associated with hemozoinnanoparticles within at least one focal volume of a biological tissueinterrogated by an electromagnetic energy stimulus. In an embodiment,the system 100 includes, among other things, a computing device 402operably coupled to at least one sensor of the sensor component 440 andthe energy-emitting component 104, the computing device 402 configuredto provide a control signal to an energy-emitting component.

In an embodiment, the system 100 includes, among other things, anenergy-emitting component 104 configured to deliver an effective amountof a electromagnetic energy stimulus to elicit a nonlinear opticalresponse from hemozoin nanoparticles within the biological tissue, theelicited nonlinear response of a character and for a duration sufficientto modulate a biological activity of a malarial infectious agent withinthe biological tissue. In an embodiment, the elicited nonlinear responseincludes one or more peak emission wavelengths ranging from about 175nanometers to about 650 nanometers. In an embodiment, the elicitednonlinear response includes one or more peak emission wavelengthsranging from about 250 nanometers to about 270 nanometers. In anembodiment, the elicited nonlinear response includes a peak emissionwavelengths of about 260 nanometers.

In an embodiment, the elicited nonlinear response is of a character andfor a duration sufficient to induce programmed cell death of aplasmodium parasite that includes the hemozoin nanoparticles. Manyeukaryotic cells, including some unicellular organisms, undergo one ormore forms of programmed cell death. Programmed cell death can beinduced either by a stimulus such as, for example, non-repairable damageto the cell, infection, starvation, exposure to ionizing radiation, heator toxic chemicals, or by removal of a repressor agent. The initiationof programmed cell death in response to specific stimuli may represent afavorable adaptation by the organism and may confer advantage during anorganism's life-cycle. In the case of plasmodium parasite, for example,programmed cell death of a subset of the parasite population could be ameans for preventing early death of the infected host, providing theparasite sufficient time to develop and be transmitted to another vectoror host (see, e.g., Deponte & Becker, Trends Parasitol., 20:165-169,2004, which is incorporated herein by reference). By contrast, necrosisis defined as uncontrolled cell death that results from extreme physicalor chemical insult to the cell. Necrosis can be induced by mechanicaldamage, hypoxia, complement-mediated cell lysis, high temperature, andexposure to highly toxic agents. Necrosis is more likely to provoke aninflammatory response in the host as a result of catastrophic disruptionof the cell.

Various types of programmed cell death have been described including,but not limited to, apoptosis, autophagy, oncosis, pyroptosis andparaptosis. Apoptosis is characterized by a series of biochemical eventsleading to changes in cell morphology and ultimately cellular death. Thecharacteristic changes in cell morphology associated with apoptosisinclude but not limited to blebbing and fragmentation of the nucleus,formation of apoptotic bodies, changes to the cell membrane such as lossof membrane asymmetry and attachment, cell shrinkage and rounding,changes in cytoplasm density, nuclear fragmentation, chromatincondensation, chromosomal DNA fragmentation, oxidative stress, therelease of proteins (e.g., cytochrome c) from the mitochondria into thecytosol, the selective cleavage of proteins by proteases (especiallycaspases), and the activity of the proteases themselves. In contrast,autophagy is a catabolic process involving the degradation of a cell'sown components through the lysosomal machinery, characterized by theformation of large vacuoles which digest away the cellular organelles ina specific sequence prior to destruction of the nucleus. Oncosis is aregulated response to severe DNA damage leading to energy depletion,organelle swelling and cell membrane disruption. Pyroptosis is apro-inflammatory cell death pathway induced by intracellular bacteria inphagocytic cells and differs from the anti-inflammatory pathways ofapoptosis. Paraptosis is morphologically similar to necrosis withformation of cytoplasmic vacuoles and mitochondrial swelling butrequires new RNA and protein synthesis, consistent with a programmedbiochemical event. See, e.g., Durand & Coetzer, Bioinform. Biol.Insights 2:101-117, 2008, which is incorporated herein by reference.

Programmed cell death akin to apoptosis has been observed in plasmodiumparasites. For example, cultured ookinetes of Plasmodium berghei exhibitmultiple markers for apoptosis-like programmed cell death including lossof mitochondrial membrane potential, nuclear chromatin condensation, DNAfragmentation, translocation of phosphatidylserine to the outer surfaceof the cell membrane and caspase-like activity (see, e.g., Arambage, etal., Parasit. Vectors 2:32, 2009, which is incorporated herein byreference). While the genomes of plasmodium parasites appear to lackhomologs of the mammalian caspases, other proteases includingmetacaspases and calpain may play a role in mediating programmed celldeath in plasmodium parasites (see, e.g., Wu et al., Genome Res.,13:601-616, 2003; Chat et al., Mol. Biochem. Parasitol., 153:41-47,2007, which are incorporated herein by reference).

Programmed cell death akin to autophagy has also been observed inplasmodium parasites. For example, treatment of blood stage Plasmodiumfalciparum with S-nitroso-N-acetyl-penicillamine (SNAP), staurosporine,and chloroquine inhibits parasitemia and induces autophagy-likemorphology with vacuolization of cellular components (see, e.g., Totino,et al., Exp. Parasitol., 118:478-486, 2008, which is incorporated hereinby reference).

Programmed cell death can be induced by heat-shock or acute exposure totemperatures above the normal physiological range of the organism.Hyperthermia therapy between 40° C. and 60° C. can result in disorderedcellular metabolism and membrane function and in many instances, celldeath. In general, at temperatures below 60° C., hyperthermia is morelikely to induce programmed cell death without substantially inducingnecrosis. At temperatures greater than about 60° C., the likelihood ofinducing coagulation necrosis of cells and tissue increases. Relativelysmall increases in temperature, e.g., 3° C., above the normalfunctioning temperature of a cell can cause programmed cell death. Forexample, temperatures ranging from 40° C. to 47° C. can induce celldeath in a reproducible time and temperature dependent manner in cellsnormally functioning at 37° C. Elevating the temperature of a mammaliancell, for example, to 43° C. can cause changes in cellular proteinexpression and increased programmed cell death. See, e.g., Somwaru, etal., J. Androl. 25:506-513, 2004; Stankiewicz, et al., J. Biol. Chem.280:38729-38739, 2005; Sodja, et al., J. Cell Sci. 111:2305-2313, 1998;Setroikromo, et al., Cell Stress Chaperones 12:320-330, 2007; Dubinsky,et al., AJR 190:191-199, 2008; Lepock. Int. J. Hyperthermia, 19:252-266,2003; Roti Roti Int. J. Hyperthermia 24:3-15, 2008; Fuchs, et al., “TheLaser's Position in Medicine” pp 187-198 in Applied Laser Medicine. Ed.Hans-Peter Berlien, Gerhard J. Muller, Springer-Verlag New York, LLC,2003; which are all incorporated herein by reference.

Plasmodium parasites are also susceptible to programmed cell death inresponse to hyperthermia therapy. For example, established isolates ofPlasmodium falciparum as well as wild isolates derived from patientswith malaria fail to grow at a culture temperature of 40° C., withschizonts exhibiting chromatin condensation (pyknosis) andhyposegmentation (see Kwiatkowski, J. Exp. Med. 169:357-361, 1989, whichis incorporated herein by reference). It is suggested that the markedinhibition of Plasmodium falciparum growth at elevated temperature isdue to disruption of the latter half of the asexual erythrocytic cycle,with developing schizonts particularly vulnerable to heat-shock.Treatment of erythrocyte stage Plasmodium falciparum at 40° C. alsoappears to induce cytoplasmic vacuolization and disruption of theparasite's food vacuole (see, e.g., Porter et al., J. Parasitol.94:473-480, 2008). Exposure of Plasmodium falciparum to a temperature of41° C. for as little as two minutes causes relative decreases in thenumber of parasites in the ring stage, trophozoite stage, and schizontstage measured 48 hours later by 20%, 70%, and 100%, respectively (see,e.g., Joshi et al., FEBS 312:91-94, 1992, which is incorporated hereinby reference). Heating erythrocyte stage Plasmodium falciparum at 41° C.for 2, 8, and 16 hours reduces survival of the parasites by 23%, 66%,and 100%, respectively (see Oakley et al., Infection Immunity75:2012-2025, 2007, which is incorporated herein by reference). Thereduction in survival under these heat-shock conditions is accompaniedby the appearance of “crisis forms” of the parasite and a time dependincrease in positive terminal deoxynucleotidyltransferase-mediateddUTP-biotin nick end labeling (TUNEL) activity, indicators of programmedcell death. The response to heat-shock is also accompanied by changes inplasmodium parasite gene and protein expression suggesting that exposureto elevated temperature, e.g., 41° C., induces an organized signalingpathway involved in promoting programmed cell death as a response toelevated temperature. For example, mRNA and protein corresponding to thePlasmodium falciparum heat shock protein 70 (PfHSP-70) are elevated 7.42fold and 3.7 fold, respectively in response to heat-shock at 41° C. Anumber of other parasite proteins are up or down regulated in responseto hyperthermia including other stress proteins, DNA repair/replicationproteins, histones, RNA processing proteins, secretion and traffickingproteins, and various serine/threonine protein kinases (see Oakley etal., Infection Immunity 75:2012-2025, 2007, which is incorporated hereinby reference).

In some instances, programmed cell death in plasmodium parasites may beinduced by exposure to one or more drugs. For example, the anti-malarialdrug chloroquine concentrates in the plasmodium parasite food vacuolewhere it caps hemozoin molecules to prevent further biocrystallizationof heme, leading to accumulation of heme in the parasite. Chloroquinecomplexed to heme is highly toxic to the plasmodium parasite anddisrupts membrane function, causing cell lysis and ultimately parasitecell autodigestion. See, e.g., Orjih et al., Science, 214:667-669, 1981,which is incorporated herein by reference. In another example, treatmentof erythrocyte stage Plasmodium falciparum with atovaquone reduces thenumber of detectable infected erythrocytes 2- to 3-fold with aconcomitant loss in parasite mitochondrial membrane potential, a markerof programmed cell death (see Nyajeruga et al., Microbes Infect.8:1560-1568, 2006, which is incorporated herein by reference). Treatmentof erythrocyte stage Plasmodium falciparum withS-nitroso-N-acetyl-penicillamine (SNAP) induces abnormal parasite forms,“crisis forms,” and DNA degradation, also markers of programmed celldeath. The inhibition of plasmodium parasite growth and induction ofplasmodium parasite death by various anti-malarial drugs may beaccompanied by changes in the plasmodium parasite proteosome. Forexample, treatment of Plasmodium falciparum with artemisinin andchloroquine results in upregulation of 41 and 38 parasite proteinsrespectively (see, e.g., Prieto, et al., PLoS ONE, 3:e4098, 2008, whichis incorporated herein by reference). In an embodiment, the systems,devices, or methods described herein can be used sequentially, orconcurrently with anti-malarial drugs to, for example, induce programmedcell death in Plasmodium falciparum.

In an embodiment, the elicited nonlinear response is of a character andfor a duration sufficient to cause a cellular stress, a cellularstructural change (e.g., chromatin condescension, cell shrinkage,deoxyribonucleic acid fragmentation, etc.), activation of a caspasesgene, or the like, associated with the induction of programmed celldeath (e.g., apoptosis, death of a cell mediated by an intracellularprogram, or the like) of a cell, a host cell, a malarial infectiousagent, or the like.

In an embodiment, the elicited nonlinear response is of a character andfor a duration sufficient to generate antimicrobial energy. In anembodiment, nonlinear harmonic generation of ultraviolet radiation byhemozoin in a biological tissue (e.g., in vivo hemozoin) can be used toirradiate malarial parasites with antimicrobial energy. The incidentelectromagnetic energy stimulus can be focused and pulsed in order toincrease the intensity to levels sufficient for effective harmonicgeneration. In an embodiment, the time-duty-cycle can be at a low enoughlevel so that linear energy deposition of the incident light does notdamage other tissues. The treatment can occur in vivo (e.g.,transdermal, in-eye, via fiber optic, etc.) or ex vivo (e.g., blood flowthrough external device). In an embodiment, the electromagnetic energystimulus includes a narrow-bandwidth light to increase the spectralbrightness and hence the harmonic generation efficiency. In anembodiment, the electromagnetic energy is delivered via multiple pulsesto increase total output. In an embodiment, phase-matched pulse-stackingis use to combine multiple beams/pulses at target site.

In an embodiment, the elicited nonlinear response is of a character andfor a duration sufficient to generate a sterilizing energy stimulushaving one or more peak emission wavelengths in the ultraviolet range.In an embodiment, the elicited nonlinear response is of a character andfor a duration sufficient to induce programmed cell death of a host cellcarrying the malarial infectious agent.

In an embodiment, the circuitry 108 to detect the nonlinearmulti-harmonic response energy includes one or more electromagneticsensors 442. Non-limiting examples of electromagnetic sensors 442includes electromagnetic devices having a detectable response toreceived or absorbed electromagnetic energy. Electromagnetic sensors caninclude antennas (e.g., wire/loop antennas, horn antennas, reflectorantennas, patch antennas, phased array antennas, or the like)solid-state photodetectors (e.g., photodiodes, charged-coupled devices,and photoresistors), vacuum photodetectors (e.g., phototubes andphotomultipliers) chemical photodetectors (e.g., photographicemulsions), cryogenic photodetectors (e.g., bolometers),photoluminescent detectors (e.g., phosphor powders or fluorescentdyes/markers), micro-electro-mechanical systems (MEMS) detectors (e.g.,microcantilever arrays with electromagnetically responsive materials orelements) or any other devices operable to detect and/or transduceelectromagnetic energy.

In an embodiment, the circuitry 108 to detect the nonlinearmulti-harmonic response energy includes one or more sensors 442 todetect a nonlinear response profile of one or more hemozoinnanoparticles interrogated by an electromagnetic energy stimulus.Non-limiting examples of sensor 442 include charge-coupled devices,complementary metal-oxide-semiconductor devices, photodiode image sensordevices, or whispering gallery mode micro cavity devices.

In an embodiment, the circuitry 108 to detect the nonlinearmulti-harmonic response energy includes at least one of atime-integrating optical component, a linear time-integrating component,a nonlinear optical component, or a temporal auto-correlating component.In an embodiment, the circuitry 108 to detect the nonlinearmulti-harmonic response energy includes one or more one-, two-, orthree-dimensional photodiode arrays. In an embodiment, the circuitry 108to detect the nonlinear multi-harmonic response energy includes one ormore sensors 442 for detecting a nonlinear response profile of one ormore hemozoin nanoparticles within the at least one focal volume. In anembodiment, the circuitry 108 to detect the nonlinear multi-harmonicresponse energy includes at least one charge-coupled device fordetecting a nonlinear response profile of hemozoin nanoparticles withinthe at least one focal volume. In an embodiment, the circuitry 108 todetect the nonlinear multi-harmonic response energy includes at leastone spectrometer configured to detect a nonlinear spectral responseprofile of hemozoin nanoparticles within the at least one focal volume.In an embodiment, the circuitry 108 to detect the nonlinearmulti-harmonic response energy includes at least one ultraviolet-visible(UV-VIS) diode array detector for detecting a nonlinear response profileof hemozoin nanoparticles within the at least one focal volume. In anembodiment, the circuitry 108 to detect the nonlinear multi-harmonicresponse energy includes at least one high-sensitivityultraviolet-visible (UV-VIS) diode array detector for detecting anonlinear response profile of hemozoin nanoparticles within the at leastone focal volume. In an embodiment, the circuitry 108 to detect thenonlinear multi-harmonic response energy includes circuitry configuredto detect a transcutaneously emitted multi-harmonic photonic response(e.g., a nonlinear optical response to an electromagnetic energystimulus).

In an embodiment, the circuitry 108 to detect the nonlinearmulti-harmonic response energy includes a multiplet of sensors 442operable at a corresponding multiplet of wavelengths or wavelengthbands, i.e., a first sensor operable at a first wavelength/wavelengthband, a second sensor operable at a second wavelength/wavelength band,etc. In an embodiment, the circuitry 108 to detect the nonlinearmulti-harmonic response energy includes a focal plane array of sensors442 or sensor multiplets (e.g., a Bayer or Foveon sensor).

In an embodiment, the circuitry 108 to detect the nonlinearmulti-harmonic response energy includes a sensor component 440 to detecta nonlinear multi-harmonic response profile associated with hemozoinnanoparticles in a biological tissue within multiple focal volumesinterrogated by a pulsed electromagnetic energy stimulus. In anembodiment, the circuitry 108 to detect the nonlinear multi-harmonicresponse energy includes at least one sensor 442 for detecting nonlinearmulti-harmonic response energy associated with at least one of a secondharmonic response, a third harmonic response, or a fourth harmonicresponse elicited by an electromagnetic energy stimulus (e.g., a pulsedelectromagnetic energy stimulus, a spatially-patterned electromagneticenergy stimulus, a multiplexed electromagnetic energy stimulus, aspatially-patterned pulsed multiplexed electromagnetic energy stimulus,a temporally patterned electromagnetic energy stimulus, or the like).

In an embodiment, the circuitry 108 to detect the nonlinearmulti-harmonic response energy includes an optical assembly 112 and atleast one sensor 442 for collecting and detecting via an epi-collectionmode at least one of a second harmonic response, a third harmonicresponse, or a fourth harmonic response elicited by thespatially-patterned pulsed multiplexed electromagnetic energy stimulus.The optical assembly 112 can take a variety of forms and configurations.In an embodiment, the optical assembly 112 includes one or more lenses,optical elements (e.g., a beamsplitter and lens), diffractive elements(e.g. Fresnel lenses), filters, polarizers, or the like to guide andshape electromagnetic radiation from a source (e.g., an energy-emittingcomponent 104, a nonlinear optical response, or the like). In anembodiment, Dark-field illumination detection techniques can be furtherenhanced in contrast and selectivity by adding orthogonal (or crossed)polarizers to the illuminator and detector. Cross polarization limitsdetection to scattering events that depolarize the illumination, greatlyreducing false positives and unwanted signal from healthy tissue. Thisis relevant for both imaging and spectroscopic, in vivo and in vitrosystem, devices, and methods.

Non-limiting examples of lenses include cylindrical graded index (GRIN)lenses, doublet or triplet lenses, that gather and shape electromagneticradiation from a source (e.g., an energy-emitting component 104, anonlinear optical response, or the like). Where the electromagneticradiation source includes optical fibers that feed one or more lenses,the lenses are optionally bonded to or integral with the fibers.

In an embodiment, the optical assembly 112 includes one or more ofpolarization sensitive materials, chromatic correction, or other opticaltechniques for controlling the shape, phase, polarization, or othercharacteristics of the electromagnetic radiation. In an embodiment, theoptical assembly 112, includes one or more polarizers, color filters,exit pupil expanders, chromatic correction elements, eye-trackingelements, and background masks may be incorporated for certainapplication as appropriate. In an embodiment, the optical assembly 112includes at least one Rheinberg filter. In an embodiment, the opticalassembly 112 includes an objective lens assembly 114 having aselectively controllable numerical aperture ranging from about 0.5 toabout 1.4. In an embodiment, the circuitry 108 configured to detect thenonlinear multi-harmonic response energy includes a computing device 402for actively controlling a numerical aperture of an objective lensassembly 114 having a selectively controllable numerical apertureranging from about 0.5 to about 1.4. In an embodiment, the system 100includes an objective lens assembly 114 having a numerical apertureranging from about 0.5 to about 1.4.

In an embodiment, the optical assembly 112 receives a portion ofscattered radiation in a dark field collection configuration. In anembodiment, the optical assembly 112 receives a portion of scatteredradiation in a Rheinberg collection configuration. In an embodiment, theoptical assembly 112 receives a portion of scattered radiation in anepi-collection configuration. In an embodiment, the circuitry 108 todetect the nonlinear multi-harmonic response energy includes circuitryconfigured to detect, in situ, nonlinear multi-harmonic response energyassociated with hemozoin nanoparticles within the at least one focalvolume interrogated by the spatially-patterned pulsed multiplexedelectromagnetic energy stimulus.

In an embodiment, the system 100 includes, among other things, circuitry116 to compare information associated with a detected nonlinearmulti-harmonic response information to reference information configuredas a data structure 424. In an embodiment, the system 100 includes,among other things, circuitry 116 configured to compare informationassociated with a detected nonlinear multi-harmonic response informationto reference hemozoin response information configured as a datastructure 424. In an embodiment, the data structure 424 includes one ormore heuristics. In an embodiment, the one or more heuristics include aheuristic for determining a rate of change associated with at least onephysical parameter associated with a biological fluid. In an embodiment,the one or more heuristics include a heuristic for determining thepresence of hemozoin nanoparticles. In an embodiment, the one or moreheuristics include a heuristic for determining the presence of aninfectious agent. In an embodiment, the one or more heuristics include aheuristic for determining at least one dimension of an infected tissueregion. In an embodiment, the one or more heuristics include a heuristicfor determining a location of an infection. In an embodiment, the one ormore heuristics include a heuristic for determining a rate of changeassociated with a biochemical marker within the one or more focalvolumes.

In an embodiment, the one or more heuristics include a heuristic fordetermining a biochemical marker aggregation rate (e.g., a hemozoinaggregation rate, a hemozoin polymer aggregation rate, or the like). Inan embodiment, the one or more heuristics include a heuristic fordetermining a type of biochemical marker. In an embodiment, the one ormore heuristics include a heuristic for generating at least one oferythrocyte graph information, malaria-infected erythrocyte graphinformation, or hemozoin graph information.

In an embodiment, the one or more heuristics include a heuristic forgenerating at least one initial parameter. In an embodiment, the one ormore heuristics include a heuristic for forming an initial parameter setfrom one or more initial parameters. In an embodiment, the one or moreheuristics include a heuristic for generating at least one initialparameter, and for forming an initial parameter set from the at leastone initial parameter. In an embodiment, the one or more heuristicsinclude at least one pattern classification and regression protocol.

In an embodiment, at least one data structure 424 includes informationassociated with at least one parameter associated with hemozoinnonlinear optical phenomena spectral information. For example, in anembodiment, a data structure 424 includes information associated with atleast one parameter associated with at least one of hemozoin secondharmonic response spectral information, hemozoin third harmonic responsespectral information, or hemozoin fourth harmonic response spectralinformation. In an embodiment, a data structure 424 includes referenceobject information. In an embodiment, a data structure 424 includes atleast one of erythrocyte graph information, malaria-infected erythrocytegraph information, or hemozoin graph information.

In an embodiment, the system 100 includes, among other things, one ormore computer-readable media drives 426, interface sockets, UniversalSerial Bus (USB) ports, memory card slots, or the like, and one or moreinput/output components 428 such as, for example, a graphical userinterface 430, a display, a keyboard 432, a keypad, a trackball, ajoystick, a touch-screen, a mouse, a switch, a dial, or the like, andany other peripheral device. In an embodiment, the system 100 includesone or more user input/output components 428 that operably coupled to atleast one computing device 402 to control (electrical,electromechanical, software-implemented, firmware-implemented, or othercontrol, or combinations thereof) at least one parameter associated withthe energy delivery associated with the one or more energy-emittingcomponents 104. In an embodiment, the system 100 includes, among otherthings, one or more modules optionally operable for communication withone or more input/output components 428 that are configured to relayuser output and/or input. In an embodiment, a module includes one ormore instances of electrical, electromechanical, software-implemented,firmware-implemented, or other control devices. Such device include oneor more instances of memory 414, computing devices 402, ports, valves132, antennas, power, or other supplies; logic modules or othersignaling modules; gauges or other such active or passive detectioncomponents; or piezoelectric transducers, shape memory elements,micro-electro-mechanical system (MEMS) elements, or other actuators.

The computer-readable media drive 426 or memory slot may be configuredto accept signal-bearing medium (e.g., computer-readable memory media,computer-readable recording media, or the like). In an embodiment, aprogram for causing the system 100 to execute any of the disclosedmethods can be stored on, for example, a computer-readable recordingmedium (CRMM) 434, a signal-bearing medium, or the like. Non-limitingexamples of signal-bearing media include a recordable type medium suchas a magnetic tape, floppy disk, a hard disk drive, a Compact Disc (CD),a Digital Video Disk (DVD), Blu-Ray Disc, a digital tape, a computermemory, or the like, as well as transmission type medium such as adigital and/or an analog communication medium (e.g., a fiber opticcable, a waveguide, a wired communications link, a wirelesscommunication link (e.g., transmitter, receiver, transceiver,transmission logic, reception logic, etc.), etc.). Further non-limitingexamples of signal-bearing media include, but are not limited to,DVD-ROM, DVD-RAM, DVD+RW, DVD-RW, DVD-R, DVD+R, CD-ROM, Super Audio CD,CD-R, CD+R, CD+RW, CD-RW, Video Compact Discs, Super Video Discs, flashmemory, magnetic tape, magneto-optic disk, MINIDISC, non-volatile memorycard, EEPROM, optical disk, optical storage, RAM, ROM, system memory,web server, or the like.

In an embodiment, the system 100 includes signal-bearing media in theform of one or more logic devices (e.g., programmable logic devices,complex programmable logic device, field-programmable gate arrays,application specific integrated circuits, or the like) comprising, forexample, a data structure 424 including one or more look-up tables. Inan embodiment, the system 100 includes, among other things,signal-bearing media having reference hemozoin nonlinear responseinformation configured as a data structure 424. In an embodiment, thedata structure 424 includes at least one of malarial infectionindication information, hemozoin spectral information, hemozoin opticalresponse information, diseased state indication information, or diseasedtissue indication information.

The system 100 can include among other things, one or more receivers1206, transceivers 1208, transmitters 1210, or the like. In anembodiment, at least one of the one or more receivers 1206, transceivers1208, or transmitters 1210 is wirelessly coupled to a computing device402 that communicates with a control unit of the system 100 via wirelesscommunication. In an embodiment, at least one receiver 1206 ortransceiver 1208 is configured to acquire information associated with aset of targets, biomarkers, or the like for detection. In an embodiment,at least one receiver 1206 or transceiver 1208 is configured to acquireinformation associated with a set of physiological characteristic fordetection. In an embodiment, at least one receiver 1206 or transceiver1208 is configured to acquire information associated with one or morephysiological characteristics for detection. In an embodiment, at leastone receiver 1206 or transceiver 1208 is configured to acquireinformation associated with one or more hemozoin characteristics fordetection.

In an embodiment, the system 100 includes at least one transceiver 1208configured to report status information at a plurality of time intervalsin response to the comparison. In an embodiment, the system 100 includesat least one transceiver 1208 configured to request reference hemozoinnonlinear response information in response to the comparison.

In an embodiment, the system 100 includes a transmitter configured tosend comparison information associated with a comparison of detectednonlinear multi-harmonic response energy to the reference hemozoinresponse profile. In an embodiment, at least one of a receiver 1206 or atransceiver 1208 is configured to obtain information regarding a targetdetection set of one or more characteristics associated with thebiological subject. In an embodiment, the system 100 includes at leastone of a transmitter 1210, a receiver 1206, or a transceiver 1208configured to acquire magnetization-induced nonlinear optical responseinformation emitted by a biological sample. In an embodiment, the system100 includes at least on transceiver 1208 configured to concurrently orsequentially transmit or receive information.

In an embodiment, the system 100 includes, among other things, circuitry116 configured to compare information associated with a detectednonlinear multi-harmonic response energy to a reference hemozoinresponse profile. In an embodiment, the circuitry 116 for comparinginformation associated with the detected nonlinear multi-harmonicresponse energy to the reference hemozoin response profile includes oneor more computer-readable memory media having a reference hemozoinresponse profile configured as a data structure 424, the referencehemozoin response profile including at least one of hemozoin secondharmonic response spectral information, hemozoin third harmonic responsespectral information, or hemozoin fourth harmonic response spectralinformation. In an embodiment, the reference hemozoin response profileincludes reference nonlinear response information indicative of ahemozoin nanoparticle aggregation rate. In an embodiment, the referencehemozoin response profile includes reference nonlinear responseinformation indicative of a presence of a hemoglobin metaboliteincluding a heme polymer. In an embodiment, the reference hemozoinresponse profile includes reference hemozoin nanoparticle nonlinearsusceptibility information.

In an embodiment, the circuitry 116 configured to compare the detectednonlinear multi-harmonic response energy to the reference hemozoinresponse profile includes one or more computer-readable memory mediahaving a reference hemozoin response profile configured as a datastructure 424, the reference hemozoin response profile including atleast one of hemozoin nonlinear response information, hemozoin spectralinformation, or hemozoin nonlinear susceptibility information.

In an embodiment, the circuitry 116 configured to compare the detectednonlinear multi-harmonic response energy to the reference hemozoinresponse profile includes one or more computer-readable storage mediaincluding executable instructions stored thereon that, when executed ona computer, instruct a computing device 402 to (a) retrieving fromstorage one or more parameters associated with reference hemozoinnonlinear response information; and to (b) perform a comparison of adetected nonlinear multi-harmonic response profile to the retrieved oneor more parameter. In an embodiment, the one or more computer-readablestorage media further include executable instructions stored thereonthat, when executed on a computer, instruct a computing device 402 todetermine one or more of a presence, an absence, or a severity ofmalaria in response to the comparison.

In an embodiment, the circuitry 116 configured to compare the detectednonlinear multi-harmonic response energy to the reference hemozoinresponse profile includes a transmitter configured to send comparisoninformation associated with a comparison of in situ detected nonlinearmulti-harmonic response energy to the reference hemozoin responseprofile. In an embodiment, the circuitry 116 configured to compare thedetected nonlinear multi-harmonic response energy to the referencehemozoin response profile includes a transceiver 1208 configured toreceive a request to transmit at least one of hemozoin referenceinformation, in situ detected nonlinear multi-harmonic response energy,and comparison information.

In an embodiment, the circuitry 116 configured to compare the detectednonlinear multi-harmonic response energy to the reference hemozoinresponse profile includes a transceiver 1208 configured to receivehemozoin filtering information. In an embodiment, the circuitry 116configured to compare the detected nonlinear multi-harmonic responseenergy to the reference hemozoin response profile includes a transceiver1208 configured to receive spatially-patterned pulsed multiplexedelectromagnetic energy stimulus delivery parameter information. In anembodiment, the circuitry 116 configured to compare the detectednonlinear multi-harmonic response energy to the reference hemozoinresponse profile includes a transceiver 1208 configured to report statusinformation at regular or irregular time intervals. In an embodiment,the circuitry 116 configured to compare the detected nonlinearmulti-harmonic response energy to the reference hemozoin responseprofile includes circuitry configured to store paired and unpairednonlinear multi-harmonic response data. In an embodiment, the circuitry116 configured to compare the detected nonlinear multi-harmonic responseenergy to the reference hemozoin response profile includes at least oneprocessor operable to cause a storing of information associated withcomparing the nonlinear multi-harmonic response energy to the referencehemozoin response profile on one or more computer-readable storagemedia.

In an embodiment, the system 100 includes, among other things, circuitry120 configured to wirelessly communicate comparison informationassociated with comparing detected nonlinear multi-harmonic responseenergy to the reference hemozoin response profile. In an embodiment, thesystem 100 includes, among other things, circuitry 122 configured toselectively tune at least one of a wavelength distribution of thespatially-patterned pulsed multiplexed electromagnetic energy stimulusor a wavelength distribution of a collected in situ nonlinearmulti-harmonic response.

In an embodiment, the system 100 includes, among other things, circuitry124 configured to generate a response based least in part on one or morecomparisons between detected nonlinear multi-harmonic response energyand the reference hemozoin response profile. In an embodiment, theresponse includes at least one of a visual representation, an audiorepresentation (e.g., an alarm, an audio waveform representation of atissue region, or the like), a haptic representation, or a tactilerepresentation (e.g., a tactile diagram, a tactile display, a tactilegraph, a tactile interactive depiction, a tactile model (e.g., amultidimensional model of an infected tissue region, or the like), atactile pattern (e.g., a refreshable Braille display), a tactile-audiodisplay, a tactile-audio graph, or the like). In an embodiment, theresponse includes generating at least one of a visual, an audio, ahaptic, or a tactile representation of at least one of biological samplespectral information, tissue spectral information, fat spectralinformation, muscle spectral information, bone spectral information,blood component spectral information, hemozoin spectral information orthe like. In an embodiment, the response includes generating at leastone of a probability that the biological sample is infected withmalaria, or a confidence level associated with the determinedprobability that the biological sample is infected with malaria.

In an embodiment, the response includes generating at least one of avisual, an audio, a haptic, or a tactile representation of at least onephysical or biochemical characteristic associated with a biologicalsubject. In an embodiment, the response includes generating at least oneof a visual, an audio, a haptic, or a tactile representation of at leastone physical or biochemical characteristic associated with a parasiticinfection, a disease state, or the like.

In an embodiment, the response includes initiating one or more treatmentprotocols. In an embodiment, the response including initiating one ormore treatment protocols includes initiating at least one treatmentregimen. In an embodiment, the response includes delivering an energystimulus. In an embodiment, the response includes delivering an activeagent. In an embodiment, the response includes concurrently orsequentially delivering an energy stimulus and an active agent. In anembodiment, the response includes at least one of a response signal, acontrol signal, a change to a treatment parameter, or the like.

In an embodiment, the response includes a change to a character of anelectromagnetic energy stimulus. For example, in an embodiment, theresponse includes a change to at least one of a peak power, a peakirradiance, a focal spot size, a pulse width, a peak emissionwavelength, or the like. In an embodiment, the response includes achange to at least one of an electromagnetic energy stimulus intensity,an electromagnetic energy stimulus frequency, an electromagnetic energystimulus pulse frequency, an electromagnetic energy stimulus pulseratio, an electromagnetic energy stimulus pulse intensity, anelectromagnetic energy stimulus pulse duration time, an electromagneticenergy stimulus pulse repetition rate, or the like.

In an embodiment, the circuitry 124 configured to generate a responsebased least in part on one or more comparisons includes one or morereceivers 1206, transmitters 1210, transceivers 1208, or the like. In anembodiment, the circuitry 124 configured to generate a response basedleast in part on one or more comparisons includes at least one of atransmitter 1210 or a transceiver 1208 configured to send comparisoninformation associated with a comparison of detected nonlinearmulti-harmonic response energy to the reference hemozoin responseprofile. In an embodiment, the circuitry 124 configured to generate aresponse based least in part on one or more comparisons includes atleast one of a receiver 1206 or a transceiver 1208 configured to obtainreference hemozoin response profile information.

In an embodiment, the system 100 includes, among other things, circuitry126 configured to cause the generation of a magnetic field. For example,in an embodiment, the circuitry 126 includes one or more conductivetraces configured to generating a magnetic field in the presence of anapplied potential. In an embodiment, the circuitry 126 configured togenerate the magnetic field includes a radio frequency transmitterconfigured to generate a radio frequency signal. In an embodiment, thecircuitry 126 configured to generate the magnetic field includes a radiofrequency transmitter configured to generate a radio frequency signal ofa character and for a duration sufficient to magnetically align, invivo, a plurality of hemozoin nanoparticles. In an embodiment, the 126circuitry configured to generate the magnetic field includes one or morecoils configured to generate one or more radio frequency pulses.

In an embodiment, the system 100 includes, among other things, circuitry128 generate a magnetic field stimulus. In an embodiment, the circuitry128 includes a radio frequency transmitter configured to generate aradio frequency signal. In an embodiment, the circuitry 128 includes oneor more conductive traces configured to generating a magnetic field inthe presence of an applied potential. In an embodiment, the circuitry128 includes one or more coils configured to generate one or more radiofrequency pulses. In an embodiment, the circuitry 128 includes aplurality of radio frequency coils. In an embodiment, the circuitry 128a plurality of coils configured to generate a time-varying magneticfield.

In an embodiment, a generated electromagnetic field stimulus is of acharacter and for a duration sufficient to elicit hemozoin nanoparticleswithin a biological sample to deliver magnetically induced hyperthermiatherapy in vivo. Because hemozoin nanoparticles are paramagnetic, in anembodiment, applying magnetic field gradients can apply force to thehemozoin in malaria parasites. In an embodiment, applying time-varyingmagnetic fields to hemozoin can result in rapid somewhat oscillatorymovement of the hemozoin particles thereby heating the hemozoin andhence the parasites; sufficient heat to negatively affect or kill theparasites, while not being substantially affecting the normal functionof non-infected cells.

In an embodiment, the system 100 includes, among other things, circuitry130 configured to detect scattering information associated with aplurality of hemozoin nanoparticles interrogated by at least one of amultiplexed dark-field interrogation stimulus or a multiplexed Rheinberginterrogation stimulus in the presence of a magnetic field.

In an embodiment, the system 100 includes, among other things, circuitry128 configured to generate a magnetic field stimulus of a character andfor a duration sufficient to elicit hemozoin nanoparticles within abiological sample to deliver magnetically induced hyperthermia therapyin vivo.

In an embodiment, the system 100 includes, among other things, circuitry132 configured to dynamically control the magnetic field stimulus. In anembodiment, the circuitry 132 configured to dynamically control themagnetic field stimulus includes one or more processors 404 operablycoupled to the circuitry 128 configured to generate the electromagneticfield stimulus and configured to manage one or more parametersassociated with deliver of a pulsed magnetic stimulus to a region of abiological subject. In an embodiment, the circuitry 132 configured todynamically control the magnetic field stimulus includes one or moreprocessors 404 configured to regulate at least one of a delivery regimenparameter, a spaced-apart delivery pattern parameter, or a temporaldelivery pattern parameter associated with generating theelectromagnetic field stimulus.

In an embodiment, the system 100 includes, among other things, circuitry134 configured to compare a detected scattering information to referencehemozoin dark-field scattering data. In an embodiment, the circuitry 134configured to compare the nonlinear multi-harmonic response energyprofile includes one or more computer-readable memory media havingreference hemozoin nonlinear response information configured as a datastructure 424. In an embodiment, the reference hemozoin nonlinearresponse information includes modeled reference comparison information.In an embodiment, the circuitry 134 configured to compare the nonlinearmulti-harmonic response energy profile includes one or morecomputer-readable memory media having reference hemozoin nonlinearresponse information configured as a data structure 424. In anembodiment, the reference hemozoin nonlinear response informationincludes at least one of in situ detected nonlinear responseinformation, hemozoin spectral information, or hemozoin nonlinearsusceptibility information.

In an embodiment, the system 100 includes, among other things, circuitry136 configured to compare (a) a nonlinear multi-harmonic response energyprofile associated with at least one focal volume interrogated with aspatially patterned pulsed electromagnetic energy stimulus to (b)reference hemozoin nonlinear response information.

In an embodiment, the system 100 includes, among other things, circuitry138 configured to magnetically induce at least one of an oscillation, atranslation, or a rotation of hemozoin nanoparticles in a biologicalsample, the induced at least one of the oscillation, the translation,and the rotation of hemozoin nanoparticles in the biological sample of acharacter and for a duration sufficient to affect the integrity of anorganelle of a plasmodium parasite. In an embodiment, the circuitry 138configured to magnetically induce at least one of an oscillation, atranslation, or a rotation of hemozoin nanoparticles in a biologicaltissue includes a flexible circuit having a one or more conductivetraces configured to generate a magnetic field in the presence of anapplied potential. In an embodiment, the circuitry 138 configured tomagnetically induce at least one of an oscillation, a translation, or arotation of hemozoin nanoparticles in a biological tissue includes aprinted circuit having a one or more conductive traces configured togenerate a magnetic field in the presence of an applied electricalcurrent. In an embodiment, the circuitry 138 configured to magneticallyinduce at least one of an oscillation, a translation, or a rotation ofhemozoin nanoparticles in a biological tissue includes at least one of areceiver 1206, transmitter 1210, or a transceiver 1208. In anembodiment, the circuitry 138 configured to magnetically induce at leastone of an oscillation, a translation, or a rotation of hemozoinnanoparticles in a biological tissue includes at least oneelectromagnet. In an embodiment, the circuitry 138 configured tomagnetically induce at least one of an oscillation, a translation, or arotation of hemozoin nanoparticles in a biological tissue includes atleast one permanent magnet.

In an embodiment, the system 100 includes, among other things, circuitry140 configured to communicate comparison information associated withcomparing the nonlinear multi-harmonic response energy profile.

In an embodiment, the system 100 includes, among other things, circuitry142 configured to communicate treatment information associated withmagnetically inducing at least one of the oscillation, the translation,and the rotation of hemozoin nanoparticles.

In an embodiment, the system 100 includes, among other things, circuitry144 configured to detect a scattered energy from a biological tissue inat least one of a dark-field detection configuration or a Rheinbergdetection configuration. In an embodiment, the circuitry 144 configuredto detect the scattered energy includes at least one sensor 442configured to receive a portion of the scattered energy in a dark-fielddetection configuration. In an embodiment, the circuitry 144 configuredto detect the scattered energy includes at least one sensor 442configured to receive a portion of the scattered energy in a Rheinbergdetection configuration. In an embodiment, the circuitry 144 configuredto detect the scattered energy includes a lens array assembly configuredreceive at least a portion of the scattered energy from the biologicalsubject. In an embodiment, the circuitry 144 configured to detect thescattered energy includes a Rheinberg differential color illuminationassembly configured receive at least a portion of the scattered energyfrom the biological subject. In an embodiment, the circuitry 144configured to detect the scattered energy includes at least oneRheinberg filter.

In an embodiment, the system 100 includes, among other things, circuitry146 configured to magnetically perturb hemozoin nanoparticles in abiological tissue in response to a comparison between detected scatteredenergy information and reference hemozoin nanoparticles scattered energyinformation. In an embodiment, the circuitry 146 configured tomagnetically perturb hemozoin nanoparticles in a biological tissueincludes a coil assembly configured to magnetically induce at least oneof an oscillation, a translation, or a rotation of hemozoinnanoparticles in a biological tissue. In an embodiment, the circuitry146 configured to magnetically perturb hemozoin nanoparticles in abiological tissue includes one or more conductive traces configured tocause at least one of an oscillation, a translation, or a rotation ofhemozoin nanoparticles in a biological tissue. In an embodiment, thecircuitry 146 configured to magnetically perturb hemozoin nanoparticlesin a biological tissue includes one or more processors 404 that, whenactivated, generate a control signal that causes the comparison betweenthe detected scattered energy and the reference hemozoin nanoparticlesscattered energy information.

In an embodiment, the system 100 includes, among other things, circuitry148 configured to impinge an effective amount of an electromagneticenergy stimulus in a dark-field configuration onto one or more regionsof a biological tissue to produce scattered energy from the biologicaltissue. In an embodiment, the circuitry 148 configured to impinge theeffective amount of an electromagnetic energy stimulus includes a lensarray assembly configured to focus one or more incident electromagneticenergy stimuli onto the biological subject and to receive scatteredenergy therefrom.

In an embodiment, the system 100 includes, among other things, circuitry150 configured to detect a nonlinear multi-harmonic response energyassociated with hemozoin nanoparticles within at least one focal volumeof a biological tissue interrogated by an electromagnetic energystimulus. In an embodiment, the circuitry 150 configured to detect thenonlinear multi-harmonic response energy includes at least onecharged-coupled device configured to detect at least one of a secondharmonic response, a third harmonic response, or a fourth harmonicresponse associated with hemozoin nanoparticles within at least onefocal volume interrogated by an electromagnetic energy stimulus. In anembodiment, the circuitry 150 configured to detect the nonlinearmulti-harmonic response energy includes at least one ultraviolet-visiblediode array detector for detecting at least one of a second harmonicresponse, a third harmonic response, or a fourth harmonic responseassociated with hemozoin nanoparticles within at least one focal volumeinterrogated by an electromagnetic energy stimulus. In an embodiment,the circuitry 150 configured to detect the nonlinear multi-harmonicresponse energy includes circuitry configured to detect atranscutaneously emitted multi-harmonic photonic response.

In an embodiment, the circuitry 150 configured to detect the nonlinearmulti-harmonic response energy includes one or more sensors 442 fordetecting a nonlinear response profile of one or more hemozoinnanoparticles within the at least one focal volume. In an embodiment,the circuitry 150 configured to detect the nonlinear multi-harmonicresponse energy includes one or more sensors 442 for detecting aspectral response of one or more hemozoin nanoparticles within the atleast one focal volume. In an embodiment, the circuitry 150 configuredto detect the nonlinear multi-harmonic response energy includescircuitry configured to detect, in situ, nonlinear multi-harmonicresponse energy associated with hemozoin nanoparticles within the atleast one focal volume interrogated by the spatially patterned pulsedmultiplexed electromagnetic energy stimulus: In an embodiment, thecircuitry 150 configured to detect the nonlinear multi-harmonic responseenergy includes an optical assembly 112 and at least one sensor 442 forcollecting and detecting via an epi-collection mode at least one of asecond harmonic response, a third harmonic response, or a fourthharmonic response elicited by the spatially patterned pulsed multiplexedelectromagnetic energy stimulus. In an embodiment, the circuitry 150configured to detect the nonlinear multi-harmonic response energyincludes an optical assembly 112 and at least one sensor 442 forcollecting and detecting via a Rheinberg detection configuration atleast one of a second harmonic response, a third harmonic response, anda fourth harmonic response elicited by the spatially patterned pulsedmultiplexed electromagnetic energy stimulus.

In an embodiment, the system 100 includes, among other things, circuitry152 configured to generate an effective amount of a pulsedelectromagnetic energy stimulus to elicit a nonlinear response fromhemozoin nanoparticles in a biological tissue within the at least onefocal volume of the biological tissue. In an embodiment, the elicitednonlinear response is of a character and for a duration sufficient tomodulate a biological activity of a malarial infectious agent.

Absorption, transmission, scattering, etc., of electromagnetic radiationvaries among biological tissues, biological samples, equipment, othermaterials, or the like. For example, the range of about 800 nanometersto about 1300 nanometers is a range where photon absorption andscattering are minimal for dermal tissue (creating a region that isoptimal for efficient optical power transfer across the skin).Accordingly, in an embodiment, the peak emission wavelength of theelectromagnetic stimulus generated by the energy-emitting component 104is chosen to maximize the delivery and detection to and from a sample ofinterest. For example, to improve transcutaneous transmission of anelectromagnetic stimulus of and subsequent detection of a generatednonlinear optical response, a peak emission wavelength ofelectromagnetic stimulus is chosen within a range of about 1000nanometers to about 1300 nanometers. This will results in a nonlinearoptical response from hemozoin ranging from about 500 nanometers toabout 650 nanometers (for second harmonic generation; one-half thewavelength); from about 333 nanometers to about 433 nanometers (forthird harmonic generation; one-third the wavelength), etc. In anembodiment, one or more peak emission wavelengths of the electromagneticstimulus generated by the energy-emitting component 104 are chosen toelicit a nonlinear optical response of hemozoin to emit within awavelength range that damages genetic material. Other ranges may be moreoptimal for efficient optical power transfer across, for example,medical equipment, medical settings, in vitro ware, or the like.

In an embodiment, the circuitry 152 configured to generate the effectiveamount of a pulsed electromagnetic energy stimulus includes at least oneof a first energy emitter having a peak emission wavelength ranging fromabout 690 nanometers to about 2100 nanometers and at least one of asecond energy emitter having a peak emission wavelength ranging fromabout 1000 nanometers to about 2000 nanometers for multiplex nonlinearresponse assaying. In an embodiment, the circuitry 152 configured togenerate the effective amount of a pulsed electromagnetic energystimulus includes an energy-emitting component 104 configured tointerrogate at least one focal volume with a spatially patterned pulsedmultiplexed electromagnetic energy stimulus.

In an embodiment, the circuitry 152 configured to generate the effectiveamount of a pulsed electromagnetic energy stimulus includes one or morelasers, laser diodes, and light-emitting diodes. In an embodiment, thecircuitry 152 configured to generate the effective amount of a pulsedelectromagnetic energy stimulus includes one or more quantum dots,organic light-emitting diodes, microcavity light-emitting diodes, andpolymer light-emitting diodes. In an embodiment, the circuitry 152configured to generate the effective amount of a pulsed electromagneticenergy stimulus includes one or more femtosecond lasers. In anembodiment, the circuitry 152 configured to generate the effectiveamount of a pulsed electromagnetic energy stimulus includes a patternedenergy-emitting source. In an embodiment, the circuitry 152 configuredto generate the effective amount of a pulsed electromagnetic energystimulus includes a lens array configured to deliver a spaced-apartenergy stimuli having at least a first region and a second region, thesecond region having a focal depth different from the first region.

In an embodiment, the system 100 includes, among other things, circuitry154 configured to generate a multiplexed pulsed electromagnetic energystimulus having a peak power ranging from about 400 gigawatts to about 8terawatts.

In an embodiment, the system 100 includes, among other things, circuitry156 configured to direct the multiplexed pulsed electromagnetic energystimulus on a plurality of focal volumes in a biological subject.

In an embodiment, the system 100 includes, among other things, circuitry158 configured to detect a multi-harmonic response associated with aplurality of hemozoin nanoparticles in a biological tissue within one ormore of the plurality of focal volumes interrogated by the multiplexedpulsed electromagnetic energy stimulus. In an embodiment, the circuitry158 configured to detect the multi-harmonic response includes at leastone epi-direction sensor for detecting, in situ, an emittedmulti-harmonic response associated with the plurality of hemozoinnanoparticles in a biological tissue interrogated by the multiplexedpulsed electromagnetic energy stimulus.

In an embodiment, the system 100 includes, among other things, amagnetic field component 160 configured to generate a magnetic field ofa character and for a duration sufficient to magnetically align, invivo, a plurality of hemozoin nanoparticles. In an embodiment, themagnetic field component 160 includes a radio frequency transmitterconfigured to generate a radio frequency signal. In an embodiment, themagnetic field component 160 includes one or more coils configured togenerate one or more radio frequency pulses. In an embodiment, themedical diagnostic device is configured for removable attachment to abiological surface of a biological subject.

In an embodiment, the system 100 includes, among other things, aphysical coupling element configured to removably-attach at least one ofthe dark-field electromagnetic energy emitting component, the magneticfield component, and the optical energy sensor component to a biologicalsurface of a biological subject.

In an embodiment, the system 100 includes, among other things, anactively-controllable magnetic field generator 162 configured to delivera varying magnetic field stimulus at a dose sufficient to cause heatgeneration from hemozoin nanoparticles within a biological sample. In anembodiment, the actively-controllable magnetic field generator 162includes circuitry configured to generate and deliver an electromagneticenergy stimulus of a character and for a duration sufficient to causehemozoin nanoparticles within the biological sample interrogated by anelectromagnetic energy stimulus to generate thermal energy. In anembodiment, the actively-controllable magnetic field generator 162includes an electrical coil assembly that, when energized, generates amagnetic field of a character and for a duration to induce one or moreof the Brownian process and the Neélian process within the biologicalsample including hemozoin nanoparticles. In an embodiment, theactively-controllable magnetic field generator 162 includes a magneticfield generating coil assembly for applying a varying magnetic field. Inan embodiment, the actively-controllable magnetic field generator 162includes a volume coil arrangement including a plurality of coils forgenerating a circularly polarized magnetic field. In an embodiment, theactively-controllable magnetic field generator 162 includes one or moreelectromagnets.

In an embodiment, the actively-controllable magnetic field generator 162includes one or more alternating current electromagnets. In anembodiment, the actively-controllable magnetic field generator 162includes one or more coils that are configured to generate a magneticfield of a character and for a duration sufficient to increase thetemperature of a region within a plasmodium parasite including thehemozoin nanoparticles by about 3° C. to about 22° C. In an embodiment,the actively-controllable magnetic field generator 162 includes one ormore coils that are configured to generate a magnetic field of acharacter and for a duration sufficient to increase the temperature of ahemozoin-containing-region within a plasmodium parasite existing withinthe biological sample by about 3° C. to about 10° C. In an embodiment,the actively-controllable magnetic field generator 162 includes one ormore coils that are configured to generate a magnetic field of acharacter and for a duration sufficient to increase the temperature of aregion within a plasmodium parasite including the hemozoin nanoparticlesby about 3° C. to about 4° C.

In an embodiment, the actively-controllable magnetic field generator 162generatesa magnetic field of a character and for a duration sufficientto cause a temperature increase within a region of a plasmodium parasiteincluding the hemozoin nanoparticles. In an embodiment, theactively-controllable magnetic field generator 162 generatesa magneticfield of a sufficient strength or duration to attenuate an activity of amalarial infectious agent. In an embodiment, the actively-controllablemagnetic field generator 162 provides a magnetic field of a sufficientstrength or duration to modulate heme polymerase activity of a malarialinfectious agent.

In an embodiment, the actively-controllable magnetic field generator 162provides a magnetic field of a character and for a duration sufficientto ameliorate a plasmodium parasitic effect without substantiallydisrupting the integrity of an erythrocyte encapsulating a plasmodiumparasite. In an embodiment, the actively-controllable magnetic fieldgenerator 162 provides a magnetic field of a character and for aduration sufficient to cause a temperature increase within a region of aplasmodium parasite in the biological sample, the temperature increasesufficient to cause heat-induced programmed cell death in the plasmodiumparasite.

In an embodiment, the actively-controllable magnetic field generator 162provides a magnetic field of a character and for a duration sufficientto cause programmed cell death of a host cell carrying the malarialinfectious agent. In an embodiment, the actively-controllable magneticfield generator 162 provides a magnetic field of a character and for aduration sufficient to cause a temperature increase within a region of aplasmodium parasite in the biological sample, the temperature increasesufficient to reduce a parasitemia level. In an embodiment, theactively-controllable magnetic field generator 162 generatesanalternating current magnetic field of a character and for a durationsufficient to cause a temperature increase in a region within aplasmodium parasite including the hemozoin nanoparticles and toameliorate a plasmodium parasitic effect without substantiallydisrupting the integrity of an erythrocyte encapsulating the plasmodiumparasite.

In an embodiment, the actively-controllable magnetic field generator 162includes one or more conductive coils configured to generate atime-varying magnetic field in response to an applied current, thetime-varying magnetic field of a character and for a duration sufficientto cause hemozoin nanoparticles within the biological sample to generateheat as a result of one or more of the Brownian process and the Neélianprocess. In an embodiment, the actively-controllable magnetic fieldgenerator 162 generates a magnetic field of a character and for aduration sufficient to induce heat-damage to an organelle membranewithin a plasmodium parasite within the biological sample. In anembodiment, the actively-controllable magnetic field generator 162includes at least one radio frequency transmitter including one or moreone radio frequency coils configured to generate a localized radiofrequency stimulus.

In an embodiment, the actively-controllable magnetic field generator 162is configured to concurrently or sequentially generate at least a firstelectromagnetic energy stimulus and a second electromagnetic energystimulus, the first electromagnetic energy stimulus of a character andfor a duration sufficient to magnetically align hemozoin nanoparticlesin a biological tissue, the second electromagnetic energy stimulus of acharacter and for a duration sufficient to magnetically induce at leastone of an oscillation, a translation, or a rotation of the hemozoinnanoparticles in the biological tissue. In an embodiment, the induced atleast one of the oscillation, the translation, and the rotation of thehemozoin nanoparticles in a biological tissue is sufficient to affect anintegrity of an organelle of a malarial infectious agent. In anembodiment, the induced at least one of the oscillation, thetranslation, and the rotation of the hemozoin nanoparticles in abiological tissue is sufficient to affect the integrity of a digestivefood vacuole of a malaria parasite. In an embodiment, the induced atleast one of the oscillation, the translation, and the rotation of thehemozoin nanoparticles in a biological tissue is sufficient to disruptan in vivo heme polymerization process.

In an embodiment, the system 100 includes, among other things, acomputing device 402 operatively coupled to the actively-controllablemagnetic field generator. In an embodiment, the computing device 402includes one or more processors 404 for controlling at least one of amagnetic field ON duration, a magnetic field strength, a magnetic fieldfrequency, or a magnetic field waveform.

In an embodiment, the system 100 includes, among other things, adark-field electromagnetic energy emitting component configured tointerrogate at least one focal volume of biological tissue with amulti-mode dark-field stimulus.

In an embodiment, the system 100 includes, among other things, one ormore power sources 700. In an embodiment, the power source 700 iselectromagnetically, magnetically, ultrasonically, optically,inductively, electrically, or capacitively coupleable to one or moreenergy-emitting components 104. In an embodiment, the power source 700is carried by a monitor or treatment device 102. In an embodiment, thepower source 700 comprises at least one rechargeable power source 702.In an embodiment, the power source 700 is configured to wirelesslyreceive power from a remote power supply.

In an embodiment, the monitor or treatment device 102 includes one ormore biological-subject (e.g., human)-powered generators 704. In anembodiment, the biological-subject-powered generator 704 is configuredto harvest energy from, for example, motion of one or more joints. In anembodiment, the biological-subject-powered generator 704 is configuredto harvest energy generated by the biological subject using at least oneof a thermoelectric generator 706, piezoelectric generator 708,electromechanical generator 710 (e.g., a microelectromechanical systems(MEMS) generator, or the like), biomechanical-energy harvestinggenerator 712, or the like.

In an embodiment, the biological-subject-powered generator 704 isconfigured to harvest thermal energy generated by the biologicalsubject. In an embodiment, a thermoelectric generator 706 is configuredto harvest heat dissipated by the biological subject. In an embodiment,the biological-subject-powered generator 704 is configured to harvestenergy generated by any physical motion or movement (e.g., walking,) bybiological subject. For example, in an embodiment, thebiological-subject-powered generator 704 is configured to harvest energygenerated by the movement of a joint within the biological subject. Inan embodiment, the biological-subject-powered generator 704 isconfigured to harvest energy generated by the movement of a fluid (e.g.,biological fluid) within the biological subject.

Among power sources 700 examples include, but are not limited to, one ormore button cells, chemical battery cells, a fuel cell, secondary cells,lithium ion cells, micro-electric patches, nickel metal hydride cells,silver-zinc cells, capacitors, super-capacitors, thin film secondarycells, ultra-capacitors, zinc-air cells, or the like. Furthernon-limiting examples of power sources 700 include one or moregenerators (e.g., electrical generators, thermo energy-to-electricalenergy generators, mechanical-energy-to-electrical energy generators,micro-generators, nano-generators, or the like) such as, for example,thermoelectric generators, piezoelectric generators, electromechanicalgenerators, biomechanical-energy harvesting generators, or the like. Inan embodiment, the monitor or treatment device 102 includes one or moregenerators configured to harvest mechanical energy from for example,ultrasonic waves, mechanical vibration, blood flow, or the like. In anembodiment, the monitor or treatment device 102 includes one or morepower receivers 732 configured to receive power from an in vivo or exvivo power source. In an embodiment, the in vivo power source includesat least one of a thermoelectric generator, a piezoelectric generator,an electromechanical energy to electricity generator, or abiomechanical-energy harvesting generator.

In an embodiment, the power source 700 includes at least one of athermoelectric generator, a piezoelectric generator, anelectromechanical generator, or a biomechanical-energy harvestinggenerator, and at least one of a button cell, a chemical battery cell, afuel cell, a secondary cell, a lithium ion cell, a micro-electric patch,a nickel metal hydride cell, silver-zinc cell, a capacitor, asuper-capacitor, a thin film secondary cell, an ultra-capacitor, or azinc-air cell. In an embodiment, the power source 700 includes at leastone rechargeable power source.

In an embodiment, a monitor or treatment device 102 includes a powersource 700 including at least one of a thermoelectric generator apiezoelectric generator, an electromechanical generator, or abiomechanical-energy harvesting generator. In an embodiment, the powersource 700 is configured to manage a duty cycle associated with emittingan effective amount of the electromagnetic energy stimulus from the oneor more energy-emitting components 104. In an embodiment, the powersource 700 is configured to manage a duty cycle associated with emittingan effective amount of a sterilizing energy stimulus from the one ormore energy-emitting components 104.

In an embodiment, the power source 700 is configured to manage a dutycycle associated with magnetically inducing at least one of anoscillation, a translation, or a rotation of hemozoin nanoparticles in abiological tissue. In an embodiment, the power source 700 is configuredto manage a duty cycle associated with comparing the nonlinearmulti-harmonic response energy profile associated with at least onefocal volume interrogated with the spatially patterned pulsedelectromagnetic energy stimulus to reference hemozoin nonlinear responseinformation. In an embodiment, the system 100 includes, among otherthings, an energy storage device. In an embodiment, the energy storagedevice includes at least one of a battery, a capacitor, or a mechanicalenergy store.

FIG. 2A shows a system 100 for modulating plasmodium parasitic activity.The system 100 for modulating plasmodium parasitic activity includes,among other things, circuitry 128 configured to generate a magneticfield stimulus of a character and for a duration sufficient to elicithemozoin nanoparticles within a biological sample to delivermagnetically induced hyperthermia therapy in situ, in vitro, in vivo, orthe like. In situ includes in vivo or in vitro. In an embodiment, thesystem 100 for modulating plasmodium parasitic activity includescircuitry 208 configured to dynamically control the magnetic fieldstimulus. In an embodiment, the circuitry 208 configured to dynamicallycontrol the magnetic field stimulus includes one or more processors 404operably coupled to the circuitry 202 configured to generate theelectromagnetic field stimulus and configured to manage one or moreparameters associated with deliver of a pulsed magnetic stimulus to aregion of a biological subject. In an embodiment, the circuitry 208configured to dynamically control the magnetic field stimulus includesone or more processors 404 configured to regulate at least one of adelivery regimen parameter, a spaced-apart delivery pattern parameter,or a temporal delivery pattern parameter associated with generating theelectromagnetic field stimulus.

FIG. 2B shows a system 100 for optically monitoring/modulating aplasmodium parasitic activity. In an embodiment, the system 100 includesa scanning/projection system 210 and a detection subsystem 212 operatingunder at least one computing device 402. The system 100 may beimplemented in a variety of formats, such as, but not limited to, anoptical scanner-based system, such as that described in one or more ofU.S. Pat. No. 6,445,362, U.S. 2006/0284790 and/or U.S. 2005/0020926.

In one approach, the scanning/projection system 210 directs one or moreelectromagnetic energy stimuli 214 through a beam splitter 216 andthrough an optical lens assembly 218 toward a biological subject's eye220. For example, the system 100 directs an effective amount of anelectromagnetic energy stimulus 214 onto one or more focal volumes of abiological subject to produce scattered radiation from the biologicalsubject, and detects using a dark field detection configuration at leasta portion of the scattered radiation 225.

In an illustrative embodiment, the system 100 employs one or moreenergy-emitting components 104, such as laser diodes or fiber coupledlasers a having a peak emission wavelength ranging from about 690nanometers to about 2100 nanometers, for at least one of theilluminating beams 214. The monitoring/modulating system 210 scans theilluminating beams 214 through a raster pattern or a Lissajous pattern,for example.

The optical lens assembly 218 couples the scanned illuminating beam 214into the eye, through its pupil where the illuminating beam of light 214strikes the retina 222. In some approaches, the optical lens assembly218 may provide a beam 224 that converges in a field of interest, suchas at or near the surface of a retina 222. In other approaches, the beammay be substantially collimated. The beam splitter 216 may be any of avariety of optical structures that can selectively transmit and/orre-direct at least a portion of light along one or more paths. In anillustrative embodiment, the beam splitter may be responsive to one ormore wavelengths of light to selectively transmit and/or re-direct atleast a portion of light. As will be described herein, some of the lightthat returns from the field of interest is collected using adifferential illumination configuration. The beam splitter 216 may beconfigured to selectively transmit to the eye light at an inputwavelength, while selectively redirecting light at a scatteredwavelength, and/or the input wavelength. Note that the beam splitter mayalso redirect all or a portion of the returned light responsive topolarization or other characteristics of light.

FIG. 3A shows a hemozoin-monitoring device 300 in which one or moremethodologies or technologies may be implemented. Thehemozoin-monitoring device 300 includes, among other things, a sensorcomponent 440 configured to detect a nonlinear multi-harmonic responseprofile associated with hemozoin nanoparticles in a biological tissuewithin multiple focal volumes interrogated by an electromagnetic energystimulus (e.g., a pulsed electromagnetic energy stimulus, aspatially-patterned electromagnetic energy stimulus, a multiplexedelectromagnetic energy stimulus, a spatially-patterned pulsedmultiplexed electromagnetic energy stimulus, a temporally patternedelectromagnetic energy stimulus, or the like). In an embodiment, thesensor component 440 is configured to detect a nonlinear multi-harmonicresponse profile using one or more differential illuminationconfigurations (e.g., dark-field illumination, Rheinberg illumination,or the like). In an embodiment, the sensor component 440 is configuredto detect a nonlinear multi-harmonic response profile using at least oneof a dark-field detection configuration or a Rheinberg detectionconfiguration. In an embodiment, the sensor component 440 is configuredto detect a spectral signature characteristic for hemozoin optionallyusing at least one of a dark-field detection configuration or aRheinberg detection configuration.

The hemozoin-monitoring device 300 can includes, among other things, oneor more computer-readable storage media including executableinstructions stored thereon that, when executed on a computer, instructa computing device 402 to retrieving from storage one or more parametersassociated with reference hemozoin nonlinear response information, andperform a comparison of a detected nonlinear multi-harmonic responseprofile to the retrieved one or more parameters. In an embodiment, thehemozoin-monitoring device 300 includes a transceiver 1208 configured toconcurrently or sequentially transmit or receive information.

FIG. 3B shows a medical diagnostic device 310 in which one or moremethodologies or technologies may be implemented. The medical diagnostic310 includes, among other things, circuitry 312 configured to generate amultiplexed pulsed electromagnetic energy stimulus having a peak powerranging from about 400 gigawatts to about 8 terawatts. In an embodiment,the medical diagnostic device 310 includes circuitry 156 configured todirect the multiplexed pulsed electromagnetic energy stimulus on aplurality of focal volumes in a biological subject. In an embodiment,the medical diagnostic device 310 includes circuitry 158 configured todetect a multi-harmonic response associated with a plurality of hemozoinnanoparticles in a biological tissue within one or more of the pluralityof focal volumes interrogated by the multiplexed pulsed electromagneticenergy stimulus.

FIG. 3C shows a medical diagnostic device 320 which one or moremethodologies or technologies may be implemented. The medical diagnosticdevice 320 includes, among other things, a dark-field electromagneticenergy emitting component 104 a. In an embodiment, the dark-fieldelectromagnetic energy emitting component 104 a is configured to delivera multi-mode dark-field interrogation stimulus to at least one bloodvessel. The medical diagnostic device 320 can includes, among otherthings, a magnetic field component 322. In an embodiment, the magneticfield component 322 generatesa magnetic field of a character and for aduration sufficient to magnetically align, in vivo, a plurality ofhemozoin nanoparticles. The medical diagnostic device 320 includes,among other things, an optical energy sensor component 440 a. In anembodiment, the optical energy sensor component 440 a is configured todetect scatter optical energy from the plurality of hemozoinnanoparticles interrogated by the multi-mode dark-field interrogationstimulus in the presence of the magnetic field.

FIG. 3D shows an in situ hemozoin-monitoring device 330 in which one ormore methodologies or technologies may be implemented. The in situhemozoin-monitoring device 330 includes, among other things, anactively-controllable excitation component 104 b configured to deliver aspatially-patterned pulsed electromagnetic energy stimulus to one ormore focal volumes and configured to elicit a non-linear multi-harmonicresponse information from hemozoin nanoparticles in a biological tissuewithin the multiple focal volumes. In an embodiment, the in situhemozoin-monitoring device 330 includes a control means 332 operablycoupled to the actively-controllable excitation 104 b component andconfigured to regulate at least one of a numerical aperture, aspaced-apart delivery pattern parameter, or a temporal delivery patternparameter associated with the delivery of the spatially-patterned pulsedelectromagnetic energy stimulus. In an embodiment, theactively-controllable excitation component 104 b is configured toregulate at least one of parameter associated with a peak power, a peakirradiance, a focal spot size, or a pulse width.

FIG. 3E shows an anti-malarial therapeutic device 340 in which one ormore methodologies or technologies may be implemented. In an embodiment,the anti-malarial therapeutic device 340 includes, among other things, asensor component 440 including at least one sensor 442 configured todetect nonlinear multi-harmonic response energy associated with hemozoinnanoparticles within at least one focal volume of a biological tissueinterrogated by an electromagnetic energy stimulus. In an embodiment,the anti-malarial therapeutic device 340 includes an energy-emittingcomponent 104 configured to deliver an effective amount of aelectromagnetic energy stimulus to elicit a nonlinear optical responsefrom hemozoin nanoparticles within the biological tissue, the elicitednonlinear response of a character and for a duration sufficient tomodulate a biological activity of a malarial infectious agent within thebiological tissue. In an embodiment, the anti-malarial therapeuticdevice 340 includes a computing device 402 operably coupled to at leastone sensor 442 of the sensor component 440 and the energy-emittingcomponent 104, the computing device 402 configured to provide a controlsignal to the energy-emitting component.

FIG. 4A shows an apparatus 460 in which one or more methodologies ortechnologies may be implemented. The apparatus 460 includes, among otherthings, an actively-controllable magnetic field generator 462 and acomputing device operatively coupled to the actively-controllablemagnetic field generator 462. In an embodiment, theactively-controllable magnetic field generator 462 is configured todeliver a varying magnetic field stimulus at a dose sufficient to causeheat generation from hemozoin nanoparticles within a biological sample.In an embodiment, the computing device 402 is operatively coupled to theactively-controllable magnetic field generator 462, and includes one ormore processors 404 for controlling at least one of a magnetic field ONduration, a magnetic field strength, a magnetic field frequency, or amagnetic field waveform.

FIG. 4B shows an apparatus 470 in which one or more methodologies ortechnologies may be implemented. In an embodiment, the apparatus 460includes a magnetic field generator 472 configured to concurrently orsequentially generate at least a first electromagnetic energy stimulusand a second electromagnetic energy stimulus, the first electromagneticenergy stimulus of a character and for a duration sufficient tomagnetically align hemozoin nanoparticles in a biological tissue, thesecond electromagnetic energy stimulus of a character and for a durationsufficient to magnetically induce at least one of an oscillation, atranslation, or a rotation of the hemozoin nanoparticles in thebiological tissue.

FIG. 5 shows an example of a method 500 for detecting a conditionassociated with plasmodium-infected erythrocytes. At 510, the method 500includes comparing, via circuitry, a nonlinear multi-harmonic responseprofile associated with at least one focal volume interrogated with aspatially-patterned pulsed electromagnetic energy stimulus to referencehemozoin nonlinear response information. At 512, comparing, usingcircuitry, the nonlinear multi-harmonic response profile associated withthe at least one focal volume interrogated with the spatially-patternedpulsed electromagnetic energy stimulus to the reference hemozoinnonlinear response information includes generating a comparison of thenonlinear multi-harmonic response profile to reference hemozoinnonlinear response information configured as a physical data structure424. At 514, comparing, using circuitry, the nonlinear multi-harmonicresponse profile associated with the at least one focal volumeinterrogated with the spatially-patterned pulsed electromagnetic energystimulus to the reference hemozoin nonlinear response informationincludes comparing one or more of an elicited second harmonic response,an elicited third harmonic response, and an elicited fourth harmonicresponse to the reference hemozoin nonlinear response information. At516, comparing, using circuitry, the nonlinear multi-harmonic responseprofile, associated with the at least one focal volume interrogated withthe spatially-patterned pulsed electromagnetic energy stimulus to thereference hemozoin nonlinear response information includes comparing atleast one of an in situ detected second harmonic response, an in situdetected third harmonic response, and an in situ detected fourthharmonic response to the reference hemozoin nonlinear responseinformation. At 518, comparing, using circuitry, the nonlinearmulti-harmonic response profile associated with the at least one focalvolume interrogated with the spatially-patterned pulsed electromagneticenergy stimulus to the reference hemozoin nonlinear response informationincludes comparing a detected nonlinear photonic response to thereference hemozoin nonlinear response information.

At 520, the method 500 can further include generating a response basedon the comparison of the detected nonlinear multi-harmonic responseenergy to the reference hemozoin nonlinear response information. At 522,generating the response includes providing at least one of a visual, anaudio, a haptic, or a tactile representation of a nonlinearmulti-harmonic response profile associated with the at least one focalvolume interrogated with the spatially-patterned pulsed electromagneticenergy stimulus. At 524, generating the response includes determiningone or more of a presence, an absence, or a severity of malariacondition based on the comparison of the detected nonlinearmulti-harmonic response energy to the reference hemozoin nonlinearresponse information. At 526, generating the response includesdetermining a malaria infection score based on the comparison of thedetected nonlinear multi-harmonic response energy to the referencehemozoin nonlinear response information.

FIG. 6 shows an example of a method 600. At 610, the method 600 includesinterrogating at least one focal volume suspected of containinghemozoin, with a spatially-patterned pulsed electromagnetic energystimulus. At 620, the method 600 can further include comparing, usingcircuitry, information associated with a nonlinear multi-harmonicresponse of the at least one focal volume suspected of containinghemozoin, to information associated With a reference hemozoin nonlinearresponse. At 630, the method 600 can further include determining, usingcircuitry, whether the information associated with the nonlinearmulti-harmonic response of the at least one focal volume suspected ofcontaining hemozoin, is substantially similar to information associatedwith a reference hemozoin nonlinear response. At 640, the method 600 canfurther include communicating to a user at least one result of thecomparison.

FIG. 7 shows an example of a method 700. At 710, the method 700 includeseliciting a nonlinear multi-harmonic response from hemozoinnanoparticles in a biological tissue within a focal volume byinterrogating the focal volume with a pulsed electromagnetic energystimulus having a resolution [0.61*(peak emission wavelength/numericalaperture)] ranging from about 300 nanometers to about 10 micrometers. At712, eliciting the nonlinear multi-harmonic response includes deliveringa pulsed multiplexed electromagnetic energy stimulus to multiple focalvolumes, the pulsed multiplexed electromagnetic energy stimulus of acharacter and for a duration sufficient to elicit a nonlinearmulti-harmonic response from hemozoin nanoparticles present with the atleast one focal volume. At 720, the method 700 can further includecomparing, using circuitry, the nonlinear multi-harmonic response toreference hemozoin nonlinear response information configured as aphysical data structure 424. At 722, comparing, using circuitry, thenonlinear multi-harmonic response to the reference hemozoin nonlinearresponse information includes comparing a detected second harmonicresponse to reference hemozoin second harmonic response informationconfigured as a physical data structure 424. At 724, comparing, usingcircuitry, the nonlinear multi-harmonic response to the referencehemozoin nonlinear response information includes comparing a detectedthird harmonic response to reference hemozoin third harmonic responseinformation configured as a physical data structure 424. At 726,comparing, using circuitry, the nonlinear multi-harmonic response to thereference hemozoin nonlinear response information includes comparing adetected fourth harmonic response to reference hemozoin fourth harmonicresponse information configured as a physical data structure 424.

At 730, the method 700 can further include generating a response basedon the comparison of the nonlinear multi-harmonic response to thereference hemozoin nonlinear response information.

FIG. 8 shows an example of a method 800. At 810, the method 800 includescomparing, using circuitry, information associated with a nonlinearmulti-harmonic response of at least one focal volume suspected ofcontaining hemozoin, the at least one focal volume interrogated with aspatially-patterned pulsed electromagnetic energy stimulus, toinformation associated with a reference hemozoin nonlinearmulti-harmonic response.

FIG. 9 shows an example of an in situ method 900. At 910, the method 900includes detecting, via one or more sensors 442, non-linearmulti-harmonic response information associated with multiple focalvolumes interrogated with a spatially-patterned pulsed electromagneticenergy stimulus. At 920, the method 900 can includes determining whetherthe detected non-linear multi-harmonic response information associatedwith the multiple focal volumes interrogated with thespatially-patterned pulsed electromagnetic energy stimulus satisfiesthreshold criteria associated with an absence, presence, or severity ofhemozoin nanoparticles in a biological tissue. At 930, the method 900can further includes generating a response in response to determiningwhether the detected non-linear multi-harmonic response informationassociated with the multiple focal volumes interrogated with thespatially-patterned pulsed electromagnetic energy stimulus satisfiesthreshold criteria associated with the presence of hemozoinnanoparticles in a biological tissue.

FIG. 10 shows an example of a method 1000. At 1010, the method 1000includes selectively energizing a plurality of focal volumes within abiological subject with a pulsed multiplexed electromagnetic energystimulus, the pulsed multiplexed electromagnetic energy stimulus of acharacter and for a duration sufficient to elicit a multi-harmonicresponse from hemozoin nanoparticles carried by a parasite within one ormore of the plurality of focal volumes. At 1012, selectively energizingthe plurality of focal volume includes delivering a pulsedelectromagnetic energy stimulus of a character and for a durationsufficient to elicit one or more of a second harmonic response, a thirdharmonic response, or a fourth harmonic response from hemozoinnanoparticles carried by a parasite. At 1020, the method 1000 includesgenerating a comparison between an elicited multi-harmonic response orhemozoin multi-harmonic signature information.

FIG. 11 shows an example of a method 1100. At 1110, the method 1100includes concurrently generating a multi-mode dark-field interrogationstimulus and a magnetic field stimulus. At 1120, the method 1100includes detecting a scattering response associated with a plurality ofhemozoin nanoparticles interrogated by the multiplexed dark-fieldinterrogation stimulus in the presence of the magnetic field. At 1130,the method 1100 can further include varying a direction of the magneticfield stimulus. At 1140, the method 1100 can further include detectingscattering response associated with the plurality of hemozoinnanoparticles interrogated by the multiplexed dark-field interrogationstimulus in the presence of the varying magnetic field. At 1150, themethod 1100 can further include varying a strength of the magnetic fieldstimulus.

At 1160, the method 1100 can further include detecting a scatteringresponse associated with the plurality of hemozoin nanoparticlesinterrogated by the multiplexed dark-field interrogation stimulus in thepresence of the varying magnetic field. At 1162, detecting thescattering response includes detecting a polarization of emergingscattering information. At 1164, detecting the scattering responseincludes detecting at least one of a diffracted, a reflected, or arefracted light associated with the plurality of hemozoin nanoparticlesinterrogated by the multiplexed dark-field interrogation stimulus in thepresence of the magnetic field.

FIG. 12 shows an example of a method 1200. At 1210, the method 1200includes concurrently generating a multi-mode dark-field interrogationstimulus of a character and for a duration sufficient to elicit adark-field scattering response from hemozoin nanoparticles in abiological tissue and a magnetic field stimulus of a character and for aduration sufficient to magnetically align hemozoin nanoparticles in abiological tissue.

At 1220, the method 1200 includes detecting scattered electromagneticradiation associated with a plurality of target regions within abiological subject interrogated by the multiplexed dark-fieldinterrogation stimulus in the presence of the magnetic field stimulus.

FIG. 13 shows an example of a method 1300 of heat-shocking a plasmodiumparasite. At 1310, the method 1300 includes delivering a time varyingmagnetic field energy to the biological subject, the time varyingmagnetic field energy sufficient to cause hemozoin nanoparticles in theplasmodium parasite to generate thermal energy.

FIG. 14 shows an example of a method 1400 of treating a biologicalsubject suspected of being infected with a plasmodium parasite. At 1410,the method 1400 includes delivering targeted magnetic heating within abiological subject suspected of having a plasmodium parasite bysufficiently varying an applied magnetic field so as to cause hemozoinnanoparticles within a plasmodium parasite to generate thermal energy.At 1412, delivering the targeted magnetic heating includes providing analternating external magnetic field stimulus via one or more magneticenergy-emitting components to one or more regions of a biologicalsubject suspected of having a malaria infection, the alternatingexternal magnetic field stimulus of a character and for a durationsufficient to cause heat-induced programmed cell death of plasmodiumparasites. At 1414, delivering the targeted magnetic heating includesdelivering a time-varying external magnetic field to one or more regionsof the biological subject suspected of having hemozoin. At 1416,delivering the targeted magnetic heating includes delivering atime-varying spatially focused external magnetic field to one or moreregions of the biological subject suspected of having hemozoin. At 1418,delivering the targeted magnetic heating includes delivering aneffective dose of a pulsed magnetic field stimulus to cause one or moreof Brown relaxation and Neél relaxation of hemozoin nanoparticles in abiological tissue, the effective dose sufficient to increase thetemperature in a region within the plasmodium parasite by about 3° C. toabout 22° C. At 1420, delivering the targeted magnetic heating includesdelivering an effective dose of a pulsed magnetic field stimulus toinduce one or more of Brown relaxation and Neél relaxation of hemozoinnanoparticles in a biological tissue, the effective dose sufficient toincrease the temperature in a region within the plasmodium parasite byabout 3° C. to about 10° C. At 1422, delivering the targeted magneticheating includes delivering an effective dose of the pulsed magneticstimulus to induce one or more of Brown relaxation and Neél relaxationof hemozoin nanoparticles in a biological tissue, the effective dosesufficient to increase the temperature in a region within the plasmodiumparasite by about 3° C. to about 4° C. At 1424, delivering the targetedmagnetic heating includes delivering a focused magnetic energy stimulusvia a radio frequency transmitter to the biological subject suspected ofhaving hemozoin. At 1426, delivering the targeted magnetic heatingincludes varying at least one of a duty cycle, a magnetic fieldstrength, a magnetic field frequency, or a magnetic field waveformassociated with the applied external magnetic field.

FIG. 15 shows an example of a method 1500 of enhancing a Brownian orNeelian process of a hemozoin nanoparticle. At 1510, the method 1500includes comparing, using circuitry, (a) a nonlinear multi-harmonicresponse profile information associated with at least one focal volumeinterrogated with a spatially patterned pulsed electromagnetic energystimulus to (b) a reference hemozoin nonlinear response information. At1520, the method 1500 includes applying a varying magnetic field to theat least one focal volume, the varying magnetic field energy sufficientto cause hemozoin nanoparticles to at least one of oscillate, atranslate, or a rotate.

FIG. 16 shows an example of a method 1600 of method of treating aplasmodium parasitic infection. At 1610, the method 1600 includescomparing, using circuitry, (a) a nonlinear multi-harmonic responseprofile information associated with at least one focal volumeinterrogated with a spatially patterned pulsed electromagnetic energystimulus to (b) a reference hemozoin nonlinear response information. At1620, the method 1600 includes magnetically inducing at least one of anoscillation, a translation, or a rotation of hemozoin nanoparticles inthe at least one focal volume. At 1622, magnetically inducing the atleast one of the oscillation, the translation, and the rotation ofhemozoin nanoparticles in the at least one focal volume includesenergizing one or more conductive coils for a duration sufficient togenerate a time-varying magnetic field of a character and for a durationsufficient to cause hemozoin nanoparticles to at least one of oscillate,translate, and rotate. At 1624, magnetically inducing the at least oneof the oscillation, the translation, and the rotation of hemozoinnanoparticles in the at least one focal volume includes delivering aneffective dose of a pulsed magnetic field stimulus to affect theintegrity of an organelle of a malarial infectious agent based in parton the comparison of the nonlinear multi-harmonic response profileassociated with the at least one focal volume to the reference hemozoinnonlinear response information. At 1626, magnetically inducing the atleast one of the oscillation, the translation, and the rotation ofhemozoin nanoparticles in a biological tissue includes providing a radiofrequency coil assembly an effective amount of an applied current, theeffective amount of an applied current of a character and for a durationsufficient to generate a magnetic field of a character and for aduration sufficient to cause one or more of oscillation, translation,and rotation of hemozoin nanoparticles in a biological tissue. At 1628,magnetically inducing the at least one of the oscillation, thetranslation, and the rotation of hemozoin nanoparticles in a biologicaltissue includes delivering an effective dose of a pulsed magnetic fieldstimulus to cause one or more of oscillation, translation, and rotationof hemozoin nanoparticles in a biological tissue. At 1630, magneticallyinducing the at least one of the oscillation, the translation, and therotation of hemozoin nanoparticles in a biological tissue includesdelivering an effective dose of an electromagnetic energy stimulus tocause one or more of oscillation, translation, and rotation of hemozoinnanoparticles in a biological tissue.

FIG. 17 shows an example of a method 1700. At 1710, the method 1700includes generating a comparison between (a) a detected scatteringprofile information associated with a plurality of target regions withina biological tissue interrogated by a dark-field interrogation stimulusin the presence of a magnetic field stimulus and (b) reference hemozoindark field scattering information. At 1712, generating the comparisonincludes comparing, using circuitry, a detected scattering profileassociated with a plurality of target regions within a biologicalsubject interrogated by a multiplexed dark-field interrogation stimulusin the presence of a magnetic field stimulus and reference hemozoin darkfield scattering information. At 1714, generating the comparisonincludes comparing, using circuitry, a detected scattering profileobtained using a Rheinberg illumination configuration in the presence ofa magnetic field stimulus and reference hemozoin Rheinberg illuminationspectral information.

At 1720, the method 1700 includes magnetically perturbing hemozoinnanoparticles in the biological tissue based in part on the comparison.At 1722, magnetically perturbing the hemozoin nanoparticles in abiological tissue includes applying a magnetic field stimulus of acharacter and for a duration sufficient to cause the hemozoinnanoparticles in a biological tissue to affect the integrity of adigestive food vacuole of a malaria parasite. At 1724, magneticallyperturbing the hemozoin nanoparticles in a biological tissue includesapplying an alternating magnetic field stimulus of a character and for aduration sufficient to cause the hemozoin nanoparticles in a biologicaltissue to rupture a membrane of a digestive food vacuole of a malariaparasite. At 1726, magnetically perturbing the hemozoin nanoparticles ina biological tissue includes applying a time-varying magnetic fieldstimulus of a character and for a duration sufficient to cause areduction in a parasitemia level.

FIG. 18 shows an example of a method 1800 for modulating plasmodiumparasitic activity. At 1810, the method 1800 includes eliciting anonlinear multi-harmonic response from hemozoin nanoparticles in abiological tissue by interrogating a plurality of focal volumes with apulsed electromagnetic energy stimulus having a peak irradiance of lessthan about 200 gigawatts/cm̂2 and having at least one peak emissionwavelength ranging from about 690 nanometers to about 2100 nanometers,the pulsed electromagnetic energy stimulus of a character and for aduration sufficient to modulate a biological activity of a malarialinfectious agent. At 1812, eliciting the nonlinear multi-harmonicresponse from hemozoin nanoparticles in a biological tissue includesirradiating hemozoin nanoparticles in a biological tissue within one ormore of the plurality of focal volumes with electromagnetic energyhaving a peak emission wavelength ranging from about 1000 nanometers toabout 1300 nanometers. At 1814, eliciting the nonlinear multi-harmonicresponse from hemozoin nanoparticles in a biological tissue includesirradiating hemozoin nanoparticles in a biological tissue within one ormore of the plurality of focal volumes with electromagnetic energyhaving a peak emission wavelength ranging from about 1000 nanometers toabout 1080 nanometers. At 1816, eliciting the nonlinear multi-harmonicresponse from hemozoin nanoparticles in a biological tissue includesirradiating hemozoin nanoparticles in a biological tissue within one ormore of the plurality of focal volumes with electromagnetic energyhaving a peak emission wavelength ranging from about 1012 nanometers toabout 1060 nanometers. At 1818, eliciting the nonlinear multi-harmonicresponse from hemozoin nanoparticles in a biological tissue includesirradiating hemozoin nanoparticles in a biological tissue within one ormore of the plurality of focal volumes with electromagnetic energyhaving a peak emission wavelength of about 1040 nanometers. At 1820,eliciting the nonlinear multi-harmonic response from hemozoinnanoparticles in a biological tissue includes irradiating hemozoinnanoparticles in a biological tissue within one or more of the pluralityof focal volumes with electromagnetic energy having a peak emissionwavelength ranging from about 700 nanometers to about 870 nanometers. At1822, eliciting the nonlinear multi-harmonic response from hemozoinnanoparticles in a biological tissue includes irradiating hemozoinnanoparticles in a biological tissue within one or more of the pluralityof focal volumes with electromagnetic energy having a peak emissionwavelength ranging from about 750 nanometers to about 810 nanometers. At1824, eliciting the nonlinear multi-harmonic response from hemozoinnanoparticles in a biological tissue includes irradiating hemozoinnanoparticles in a biological tissue within one or more of the pluralityof focal volumes with electromagnetic energy having a peak emissionwavelength ranging from about 760 nanometers to about 780 nanometers. At1826, eliciting the nonlinear multi-harmonic response from hemozoinnanoparticles in a biological tissue includes irradiating hemozoinnanoparticles in a biological tissue within one or more of the pluralityof focal volumes with electromagnetic energy having a peak emissionwavelength of about 780 nanometers. At 1828, eliciting the nonlinearmulti-harmonic response from hemozoin nanoparticles in a biologicaltissue includes irradiating the hemozoin nanoparticles in a biologicaltissue within one or more of the plurality of focal volumes withelectromagnetic energy of a character and for a duration to cause aportion of the hemozoin nanoparticles in a biological tissue to generatea nonlinear multi-harmonic response having a wavelength ranging fromabout 233 nanometers to about 434 nanometers. At 1830, eliciting thenonlinear multi-harmonic response from hemozoin nanoparticles in abiological tissue includes irradiating the hemozoin nanoparticles in abiological tissue within one or more of the plurality of focal volumeswith electromagnetic energy of a character and for a duration to cause aportion of the hemozoin nanoparticles in a biological tissue to generatea nonlinear multi-harmonic response having a wavelength ranging fromabout 175 nanometers to about 325 nanometers.

At 1832, eliciting the nonlinear multi-harmonic response from hemozoinnanoparticles in a biological tissue includes irradiating the hemozoinnanoparticles in a biological tissue within one or more of the pluralityof focal volumes with electromagnetic energy of a character and for aduration to cause a portion of the hemozoin nanoparticles in abiological tissue to generate a nonlinear multi-harmonic response havinga wavelength ranging from about 175 nanometers to about 290 nanometers.At 1834, eliciting the nonlinear multi-harmonic response from hemozoinnanoparticles in a biological tissue includes eliciting one or more of asecond harmonic response, a third harmonic response, or a fourthharmonic response by interrogating the hemozoin nanoparticles in abiological tissue with a pulsed electromagnetic energy stimulus, theelicited one or more of the second harmonic response, the third harmonicresponse, and the fourth harmonic response of a character and for aduration sufficient to induce programmed cell death of an infectiousagent. At 1836, eliciting the nonlinear multi-harmonic response fromhemozoin nanoparticles in a biological tissue includes eliciting one ormore of a second harmonic response, a third harmonic response, or afourth harmonic response by interrogating the hemozoin nanoparticles ina biological tissue with a pulsed electromagnetic energy stimulus, theelicited one or more of the second harmonic response, the third harmonicresponse, and the fourth harmonic response of a character and for aduration sufficient to induce apoptosis of a host cell carrying aninfectious agent. At 1838, eliciting the nonlinear multi-harmonicresponse from hemozoin nanoparticles in a biological tissue includesapplying an electromagnetic energy stimulus of a sufficient strength andduration to elicit the hemozoin nanoparticles in a biological tissuewithin a biological sample to generate antimicrobial energy. At 1840,eliciting the nonlinear multi-harmonic response from hemozoinnanoparticles in a biological tissue includes applying anelectromagnetic energy stimulus of a sufficient strength and duration tocause a nonlinear multi-harmonic response of a character and for aduration sufficient to inhibit proliferation of a malarial infectiousagent. At 1842, eliciting the nonlinear multi-harmonic response fromhemozoin nanoparticles in a biological tissue includes irradiatinghemozoin nanoparticles in a biological tissue within one or more of theplurality of focal volumes with electromagnetic energy having aresolution [0.61*(peak emission wavelength/numerical aperture)] rangingfrom about 300 nanometers to about 10 micrometers.

FIG. 19 shows an example of an anti-malarial therapeutic method 1900. At1910, the method 1900 includes applying an electromagnetic energystimulus of a sufficient strength and duration to elicit hemozoinnanoparticles within a biological sample to generate an in vivoantimicrobial energy stimulus in response to .a determination thathemozoin nanoparticles are present within the biological sample. At1912, applying the electromagnetic energy stimulus includes deliveryingan electromagnetic energy stimulus having a peak irradiance of less thanabout 200 gigawatts/cm̂2 to less than about 200 Gigawatts/cm̂2. At 1914,applying the electromagnetic energy stimulus includes deliverying apulse duration having a femtosecond pulse frequency of about 8megahertz, a peak emission wavelength ranging from about 690 nanometersto about 2100 nanometers, and a resolution [0.61*(peak emissionwavelength/numerical aperture)] ranging from about 300 nanometers toabout 10 micrometers. At 1916, applying the electromagnetic energystimulus includes generating electromagnetic energy stimulus having apeak emission wavelength ranging from 1200 nanometers to about 1300nanometers. At 1918, applying the electromagnetic energy stimulusincludes generating electromagnetic energy stimulus having a peakemission wavelength ranging from 700 nanometers to about 1000nanometers.

At least a portion of the devices and/or processes described herein canbe integrated into a data processing system. A data processing systemgenerally includes one or more of a system unit housing, a video displaydevice, memory such as volatile or non-volatile memory, processors 404such as microprocessors or digital signal processors, computationalentities such as operating systems, drivers, graphical user interfaces,and applications programs, one or more interaction devices (e.g., atouch pad, a touch screen, an antenna, etc.), and/or control systemsincluding feedback loops and control motors (e.g., feedback fordetecting position and/or velocity, control motors for moving and/oradjusting components and/or quantities). A data processing system may beimplemented utilizing suitable commercially available components, suchas those typically found in data computing/communication and/or networkcomputing/communication systems.

As shown in Example 1, nonlinear optical response information, spectralinformation, or the like associated with for example, hemozoinnanoparticles can be determined by one or more in vivo or in vitrotechnologies or methodologies.

EXAMPLE 1 In Vitro Analysis of Hemozoin Nanoparticles

A method is described for detecting nonlinear multi-harmonic responseenergy properties of materials having hemozoin nanoparticles. For thisanalysis, synthetic hemozoin crystals were crushed into a fine powderand suspended with isopropanol in a volume ratio of five partsisopropanol to one part hemozoin crystals. A droplet of thehemozoin/isopropanol suspension was placed onto a quartz cover slip(0.25 mm thickness) and the isopropanol allowed to evaporate to generatea thin-film of hemozoin. The hemozoin thin-film was further heated at70° C. for one minute to eliminate any residual condensation. Theintegrity and distribution of hemozoin crystals in the hemozointhin-film were assessed at a magnification ranging from 20× to 100×.Crystals observed in the hemozoin thin-film ranged in size from under 1micron to about 10-20 microns.

The hemozoin thin-film was exposed to a pulsed electromagnetic energystimulus to elicit a nonlinear optical response from the hemozoinnanoparticles using the experimental configuration outlined in FIG. 20.The experimental configuration provided for a pulsed electromagneticenergy stimulus in an overall range of 690 nm to 1600 nm using aTi:Sapphire laser to scan wavelengths from 690-1040 nm and an opticalparametric oscillator (OPO). The quartz cover slip containing thehemozoin thin-film was attached to a nanoscale positioning stage toallow scanning of the sample along the optical axis (z-scan) and alongthe lateral surface (lateral scan). The sample was placed between anachromatic objective (0.58 numerical aperture) and an achromaticcondenser. A prism and filtering system were used as a spatial filter tocover peak emission wavelengths ranging from 175 nm to 650 nm.Non-linear multi-harmonic response energy from the hemozoin particleswas detected using either a spectrometer or a photomultiplier tube.Various components of the experimental configuration were linked to acontroller interface (e.g., computer) including the Ti:Sapphire laser,the OPO, the detector, and the nanoscale positioning stage.

In one set of experiments designed to measure a third harmonic response,the hemozoin thin-film was scanned along the optical axis (z-scan) andthrough the focal volume of an excitation energy of 810 nm. In thisinstance, a 100× objective with a 0.9 numerical aperture was used. Thethird harmonic response energy and excitation light were collimated,passed through a UG-11 colored glass filter (transmits wavelengths of250-350 nm and of 700-800 nm) and a 265 nm notch filter and sent to aphotomultiplier tube. The anode current from the photomultiplier tubewas directly measured with an electrometer, linearly converted to avoltage, and recorded on a computer via a data acquisition card. FIG.21A shows a representative z-scan from the hemozoin thin-film using thismethodology. Also shown is the control measurement of the quartzsubstrate. The width of the peak in both cases was less than 5 μm,consistent with a beam size of less than 800 nm (based on 100× objectiveand 0.9 numerical aperture). The magnitude of the hemozoin peak variedup to 20% depending on the size of the hemozoin crystal and the amountof the focal volume filled with hemozoin. A lateral scan (FIG. 21B) wasalso performed using the parameters described above by first performinga z-scan analysis to find a maximum third harmonic response and alateral scan was performed at this z-position. FIG. 22 shows an exampleof the third harmonic response through a lateral scan (1) of thehemozoin thin-film relative to a lateral scan (2), through the quartzsubstrate

The third harmonic response efficiency is inversely proportional to thesquare of the spot size (A_(spot) ²) and the square of the pulse width(τ²) and therefore it is important to monitor and minimize both of thesevariables. The focal volume of the pulsed electromagnetic energystimulus was profield using a standard knife-edge diffraction techniqueto measure the beam waist at several positions along the optical axis.An autocorrelater was used to measure the pulse-width of the beam. Thethird order dependence on power output from the pulsed electromagneticenergy stimulus was demonstrated by plotting the laser excitation power,P(ω)[mW] against the third harmonic response power, P(3ω) [arbitraryunits] as shown in FIG. 23. A log-log scale plot of this data generateda line with a slope of approximately 3.

The herein described subject matter sometimes illustrates differentcomponents contained within, or connected with, different othercomponents. It is to be understood that such depicted architectures aremerely examples, and that in fact, many other architectures may beimplemented that achieve the same functionality. In a conceptual sense,any arrangement of components to achieve the same functionality iseffectively “associated” such that the desired functionality isachieved. Hence, any two components herein combined to achieve aparticular functionality can be seen as “associated with” each othersuch that the desired functionality is achieved, irrespective ofarchitectures or intermedial components. Likewise, any two components soassociated can also be viewed as being “operably connected”, or“operably coupled,” to each other to achieve the desired functionality,and any two components capable of being so associated can also be viewedas being “operably coupleable,” to each other to achieve the desiredfunctionality. Specific examples of operably coupleable include, but arenot limited to, physically mateable and/or physically interactingcomponents, and/or wirelessly interactable, and/or wirelesslyinteracting components, and/or logically interacting, and/or logicallyinteractable components.

FIGS. 23A and 23B show 3^(rd) order power dependence of hemozoin plottedon (FIG. 23A linear and (FIG. 23A) log-log scale. FIG. 24 shows a 3^(rd)order dependence of hemozoin on incident power. FIG. 25 is a voxel imageof hemozoin crystals 2502 in infected red blood cells 2504. FIG. 26shows a two-dimensional spatial scan of infected and uninfectederythrocytes showing intensity peaks that correspond to hemozoincrystals in the infected cells. FIG. 27 shows Third Harmonic Generation(THG) signal from hemozoin nanoparticles suspended in water. FIG. 28shows the absolute Third Harmonic Generation (THG) power from hemozoinshowing 3^(rd) order dependence. FIG. 29 Shows Hemozoin-water ThirdHarmonic Generation (THG) intensity. FIG. 30 shows a two-dimensionalplot of Third Harmonic Generation (THG) signal as a function of sourceand detected wavelength. FIG. 31A show a malaria detection apparatus102c according to one embodiment. FIG. 31B an example of a monitor ortreatment device using an epi-detection setup. FIG. 32A shows an exampleof a monitor or treatment device using a Third Harmonic Generation (THG)detection setup. FIG. 32B shows an example of a monitor or treatmentdevice using Dark-field detection according to one embodiment.

FIG. 33 shows a malaria detection apparatus 102 c, in which one or moremethodologies or technologies can be implemented such as, for example,actively detecting or treating a malarial infection. In an embodiment,the malaria detection apparatus 102 c includes a dark-fieldreflected-illumination apparatus 3300, an optical assembly 112, and asensor component 440.

Referring to FIGS. 33 and 34, in an embodiment, the dark-fieldreflected-illumination apparatus 3300 includes dark-field illuminator3302 having, among other things, a body structure 3402 having anaperture 3404 and a plurality of waveguide assemblies 3406. In anembodiment, the dark-field illuminator 3302 is configured to deliverelectromagnetic energy through the plurality of waveguide assemblies3406 onto at least one focal region at one or more angles of incidencerelative to an optical axis of an optical assembly 112. For example, inan embodiment, the plurality of waveguide assemblies 3406 are orientedto focus electromagnetic energy onto at least one focal region, at oneor more angles of incidence relative to an optical axis of an opticalassembly 112. In an embodiment, the dark-field illuminator 3302 isconfigured to rotate about an axis substantially parallel to the opticalaxis. In an embodiment, the dark-field illuminator 3302 is configured todeliver a plurality of electromagnetic energy beams onto a focal regionat two or more azimuthal angles relative to an optical axis of anoptical assembly 112. In an embodiment, the dark-field illuminator 3302is configured to deliver electromagnetic energy at two or more angles ofincidence onto two or more focal region locations.

In an embodiment, the plurality of waveguide assemblies 3406 include oneor more electromagnetic energy waveguides 3408 configured to be coupledto at least one electromagnetic energy emitter 3410. For example, in anembodiment, one or more of the plurality of waveguide assemblies 3406include at least one sleeve member 3412 configured to receive one ormore electromagnetic energy waveguides 3408. In an embodiment, one ormore of the plurality of waveguide assemblies 3406 include at least onemember sleeve 3412 configured configure to receive one or more lenses3414, polarizers 3416, and electromagnetic energy emitters 3410.

In an embodiment, the plurality of waveguide assemblies 3406 are axiallydistributed about the aperture 3404. In an embodiment, the plurality ofwaveguide assemblies 3406 are arranged about the aperture 3404 in one ormore radially symmetric patterns. In an embodiment, the plurality ofwaveguide assemblies 3406 are arrange about the aperture 3404 in one ormore rotationally symmetric patterns. In an embodiment, the plurality ofwaveguide assemblies 3406 are arranged about the aperture 3404 in one ormore concentric patterns radially symmetric about an axis substantiallyparallel to the optical axis. In an embodiment, the plurality ofwaveguide assemblies 3406 are arranged about the aperture 3404 in one ormore concentric patterns rotationally symmetric about an axissubstantially parallel to the optical axis. In an embodiment, one ormore of the plurality of waveguide assemblies 3406 are configured tocollimate electromagnetic energy within the aperture 3404.

In an embodiment, at least one of the plurality of waveguide assemblies3406 includes at least one polarizer 3416. In an embodiment, at leastone of the plurality of waveguide assemblies 3406 includes at least onelinear polarizer. In an embodiment, at least one of the plurality ofwaveguide assemblies 3406 includes at least one circular polarizer. Inan embodiment, at least one of the plurality of waveguide assemblies3406 includes at least one adjustable polarizer.

In an embodiment, at least one of the plurality of waveguide assemblies3406 includes at least one lens 3414. In an embodiment, at least one ofthe plurality of waveguide assemblies 3406 includes at least one lens3414 configured to collimate electromagnetic energy emitted by the atleast one electromagnetic energy emitter 3410. In an embodiment, atleast one of the plurality of waveguide assemblies 3406 includes atleast one lens 3414 configured to focus electromagnetic energy emittedby the at least one electromagnetic energy emitter 3410. In anembodiment, at least one of the plurality of waveguide assemblies 3406includes at least one microlens array. In an embodiment, at least one ofthe plurality of waveguide assemblies 3406 includes at least oneplano-convex lens. In an embodiment, at least one of the plurality ofwaveguide assemblies 3406 includes at least one aspheric lens.

In an embodiment, at least one of the plurality of waveguide assemblies3406 includes at least one multi-focal lens. In an embodiment, at leastone of the plurality of waveguide assemblies 3406 includes at least onevariable-focus lens. In an embodiment, at least one of the plurality ofwaveguide assemblies 3406 includes at least one liquid lens. In anembodiment, at least one of the plurality of waveguide assemblies 3406includes at least one tunable liquid lens. In an embodiment, at leastone of the plurality of waveguide assemblies 3406 includes at least oneliquid mirror. In an embodiment, at least one of the plurality ofwaveguide assemblies 3406 includes at least oneelectrowetting-controlled liquid mirror.

In an embodiment, the electromagnetic energy emitters 3410 include oneor more energy-emitting components 104. In an embodiment, theelectromagnetic energy emitter 3410 includes at least one of a laser, alaser diode, or a light-emitting diode. In an embodiment, theelectromagnetic energy emitter 3410 includes at least one of a quantumdot, an organic light-emitting diode, a microcavity light-emittingdiode, or a polymer light-emitting diode. In an embodiment, theelectromagnetic energy emitter 3410 includes at least one femtosecondlaser.

In an embodiment, the dark-field reflected-illumination apparatus 3300includes means for removably attaching the dark-fieldreflected-illumination apparatus 3300 to an optical assembly 112. Forexample, in an embodiment, the dark-field reflected-illuminationapparatus 3300 includes a slip ring 3326, a locking member 3328, and anadapter 3330 for coupling the optical assembly 112 to the dark-fieldilluminator 3302. In an embodiment, the means for removably attachingthe dark-field reflected-illumination apparatus 3300 to an opticalassembly 112 includes a coupling structure on the dark-fieldreflected-illumination apparatus 3300 that couples to a respectivecoupling structure on optical assembly 112. For example, in anembodiment, the means for removably attaching the dark-fieldreflected-illumination apparatus 3300 to an optical assembly 112includes a coupling member having a surface defining an innerpassageway, the inner passageway sized and dimensioned to friction fitover an outer surface of an optical assembly 112. In an embodiment, themeans for removably attaching the dark-field reflected-illumination 3300apparatus to an optical assembly 112 includes at least one of a bayonetcoupling structure, a friction fit coupling structure, a snap fitcoupling structure, or a threaded coupling structure having one or moresubstructures adapted to coupled to a corresponding bayonet couplingstructure, friction fit coupling structure, snap fit coupling structure,or threaded coupling structure on an assembly 112. In an embodiment, thedark-field reflected-illumination apparatus 3300 is configure toremovably attach to an optical assembly 112 by a bayonet coupling, afriction fit coupling, a snap fit coupling, or a threaded coupling. Inan embodiment, the dark-field reflected-illumination apparatus 3300includes a coupling structure configure to removably attach thedark-field reflected-illumination apparatus to an optical assembly 112.In an embodiment, the coupling structure is configure to removablyattach the dark-field reflected-illumination apparatus to the opticalassembly 112 by a bayonet coupling, a friction fit coupling, a snap fitcoupling, or a threaded coupling.

Referring to FIG. 33, in an embodiment, the optical assembly 112includes, among other things, one or more optical assembly bodystructures 3310 coupled at one end to a detector 440 (e.g., aphotodetector, an electromagnetic energy sensors, a charged-coupleddevice, a camera, or the like), via one or more adapters 3312. In anembodiment, the optical assembly 112 includes at least one plano convexlens 3314 and at least one lens retention member 3316. In an embodiment,the optical assembly 112 includes at least one polarizer 3318 and atleast one polarizer retention member 3320. In an embodiment, the opticalassembly 112 includes at least retention member 3322 configure to securea lens assembly within an optical assembly body structure 3310. In anembodiment, the optical assembly 112 includes at least objectiveassembly 3324.

In an embodiment, the dark-field reflected-illumination apparatus 3300includes means 3304 for adjusting a dark-field illuminator distancerelative to an optical assembly 112 along an axis substantially parallelto an optical axis of the optical assembly 112. In an embodiment, themeans 3304 for adjusting the dark-field illuminator distance relative toan optical assembly 112 includes a rotatable-adjustment structure 3332sized and dimension to couple a threaded member 3334. In an embodiment,the means 3304 for adjusting the dark-field illuminator distancerelative to an optical assembly 112 includes a dark-field illuminatorsecuring member 3333 operable to constrain rotation or displacement ofthe dark-field illuminator 3302.

Referring to FIG. 35, in an embodiment, the means 3304 for adjusting thedark-field illuminator distance relative to an optical assembly 112includes a computing device 402 operably coupled to at least one of arotatable-adjustment structure, a threaded adjustment structure, or aslidable-adjustment structure. In an embodiment, the computing device402 is configured to actuate a displacement, via at least one of a oneof the rotatable-adjustment structure, the threaded adjustmentstructure, or the slidable-adjustment structure, of the dark-fieldilluminator relative to an optical assembly 112, along an axissubstantially parallel to an optical axis of the optical assembly 112.

In an embodiment, the means 3304 for adjusting the dark-fieldilluminator distance relative to an optical assembly 112 includes atleast one externally threaded annular structure configure to threadedlyengage an internally threaded annular structure that when actuated torotated relative to the externally threaded annular structure, causesthe dark-field illuminator 3302 to displace relative to an opticalassembly 112 along an axis substantially parallel to an optical axis ofthe optical assembly 112.

In an embodiment, the dark-field reflected-illumination apparatus 3300includes means 3502 for adjusting an angle of incidence ofelectromagnetic energy emitted by the plurality of electromagneticenergy waveguide assemblies 3406. In an embodiment, the means 3502 foradjusting the angle of incidence of electromagnetic energy emitted bythe plurality of electromagnetic energy waveguide assemblies includes atleast one computing device 402 operably coupled to at least one of anelectro-mechanical component, an opto-mechanical component, anelectro-optic component, or an acousto-optic component. In anembodiment, the means 3502 for adjusting the angle of incidence ofelectromagnetic energy emitted by the plurality of electromagneticenergy waveguide assemblies includes at least one computing device 402operably coupled to an electro-optic lens system.

In an embodiment, the means 3502 for adjusting the angle of incidence ofelectromagnetic energy emitted by the plurality of electromagneticenergy waveguide assemblies includes at least one computing device 402operably coupled to one or more tunable optic components. In anembodiment, the means 3502 for adjusting the angle of incidence ofelectromagnetic energy emitted by the plurality of electromagneticenergy waveguide assemblies includes a computing device 402 operablycoupled to at least one of an optical waveguide configure to change anangle of incidence of electromagnetic energy delivered by one or more ofthe plurality of waveguide assemblies 3406. In an embodiment, the means3502 for adjusting the angle of incidence of electromagnetic energyemitted by the plurality of electromagnetic energy waveguide assembliesincludes a computing device 402 operably coupled to at least one tunableliquid lens. In an embodiment, the means 3502 for adjusting the angle ofincidence of electromagnetic energy emitted by the plurality ofelectromagnetic energy waveguide assemblies includes a computing device402 operably coupled to at least one optical micro-prism. In anembodiment, the means 3502 for adjusting the angle of incidence ofelectromagnetic energy emitted by the plurality of electromagneticenergy waveguide assemblies includes a computing device 402 operablycoupled to one or more micro-lens-arrays.

In an embodiment, the dark-field reflected-illumination apparatus 3300includes means for adjusting an angle of incidence of electromagneticenergy delivered by the dark-field illuminator 3302. In an embodiment,the means 3502 for adjusting the angle of incidence of electromagneticenergy delivered by the dark-field illuminator 3302 includes a computingdevice 402 operably coupled to at least one of a mechanical-opticcomponent, an electro-optic component, or an acousto-optic component. Inan embodiment, the means 3502 for adjusting the angle of incidence ofelectromagnetic energy delivered by the dark-field illuminator 3302includes a computing device 402 operably coupled to at least one of anoptical waveguide configured to change an angle of incidence ofelectromagnetic energy delivered by one or more of the plurality ofwaveguide assemblies 3406. In an embodiment, the means 3502 foradjusting the angle of incidence of electromagnetic energy delivered bythe dark-field illuminator 3302 includes a computing device 402 operablycoupled to at least one tunable liquid lens. In an embodiment, the means3502 for adjusting the angle of incidence of electromagnetic energydelivered by the dark-field illuminator 3302 includes a computing device402 operably coupled to at least one optical micro-prism. In anembodiment, the means 3502 for adjusting the angle of incidence ofelectromagnetic energy delivered by the dark-field illuminator 3302includes a computing device 402 operably coupled to one or moremicro-lens-arrays.

In an embodiment, a malaria detection apparatus 102 c is configured todetect and count of malaria infected erythrocytes. In an embodiment, amalaria detection apparatus 102 c employs spectral learning indiagnosing to improve sensitivity and specificity of a diagnosis.

In an embodiment, a malaria detection apparatus 102 c includes anoptical assembly 112 having a sample side, a detector side, and anoptical axis therethrough; a dark-field illuminator 3302 proximate thesample side of the optical assembly 112; and means 3304 for adjusting adark-field illuminator distance relative to an optical assembly 112along an axis substantially parallel to an optical axis of the opticalassembly 112. In an embodiment, a malaria detection apparatus 102 cfincludes a detector 440 configured to capture one or more micrographsassociated with the scattered electromagnetic energy from the sampleinterrogated by the dark-field illuminator. In an embodiment, a malariadetection apparatus 102 c includes a stage assembly configured to securea sample for analysis. In an embodiment, the dark-field illuminator 3302includes a plurality of waveguide assemblies 3406, and a body structure3402 having an aperture 3404 aligned along an axis substantiallyparallel to an optical axis. In an embodiment, the optical assembly 112is configured to receive scattered electromagnetic energy from a sampleinterrogated by the dark-field illuminator 3302. In an embodiment, amalaria detection apparatus 102 c includes sample stage assemblyconfigured to receive a biological sample chamber during operation. Inan embodiment, the sample stage assembly is configured to position abiological sample along an x, y, or z direction. In an embodiment, thesample stage assembly includes a stepper motor operably coupled to acomputing device 402 and is configured to positioning a biologicalsample chamber based on a tiling protocol.

Referring to FIG. 35, in an embodiment, a system 100 includes, amongother things, a detection circuit 3602 configured to acquire one or moremicrographs of a biological sample at one or more fields of view. In anembodiment, the detection circuit 3602 includes one or more detectors440 configured to acquire one or more micrographs of a biological sampleat one or more fields of view and at one or more focal depths.

In an embodiment, the system 100 includes a resolution modificationcircuit 3604 configured to modify a pixel count of at least onemicrograph and to generate at least a first modified micrograph. In anembodiment, the resolution modification circuit 3604 includes one ormore computing devices 402 configured to modify a micrograph pixelresolution. In an embodiment, the resolution modification circuit 3604includes at least one computing device 402, and one or more datastructures 424 operable to generate and store a threshold comparisonvalue, and to generate and store a kernel for filtering a plurality ofpixels forming a micrograph based on the threshold comparison value.

In an embodiment, the system 100 includes a filter-kernel generationcircuit 3606 configured to generate a kernel for filtering a pluralityof pixels forming the first modified micrograph based on a filteringcharacteristic, and to generate at least a first significance imagerepresentative of the at least one modified micrograph.

In an embodiment, the system 100 includes an object identificationcircuit 3608 configured to identify groups of pixels in the firstsignificance image indicative of one or more objects imaged in the atleast one micrograph, and to generate one or more connected componentsof a graph representative of groups of pixels indicative of the one ormore objects imaged in the at least one micrograph. In an embodiment,the object identification circuit 3608 includes a circuit configured toidentify groups of pixels in the first significance image indicative ofat least one of a hemozoin nanoparticle, a malaria-infected erythrocyte,or a non-infected erythrocyte in the at least one micrograph. In anembodiment, the object identification circuit 3608 is configure todetermine a probability that the biological sample is infected withmalaria, and to determine a confidence level associated with thedetermined probability that the biological sample is infected withmalaria.

In an embodiment, the system 100 includes a circuit 3610 configured tocompare the generated one or more connected components of the graph toreference object information stored in one or more data structures 424,and to generate a response based on the comparison of the generated oneor more connected components of the graph to the reference objectinformation. In an embodiment, the circuit 3610 configured to comparethe generated one or more connected components of the graph includes oneor more data structures 424 having reference object information storedthereon, the reference object information including at least one oferythrocyte graph information, malaria-infected erythrocyte graphinformation, or hemozoin graph information. In an embodiment, thecircuit 3610 configured to compare the generated one or more connectedcomponents of the graph includes a circuit 3612 configured to generate aresponse including at least one of object identification information, adisease state, a parasitemia level, a erythrocyte count, a ratio ofmalaria-infected erythrocytes to total erythrocyte present in the atleast one micrograph, or probability and confidence level informationassociated with an identified object.

In an embodiment, the system 100 includes a spatial frequency generationcircuit 3614 configured to determine a spatial frequency spectrum of atleast a first subset of pixels of the at least one micrograph, comparethe spatial frequency spectrum of the first subset of pixels toreference spatial frequency spectrum information, and generate aresponse based on the comparison of the spatial frequency spectrum ofthe first subset of pixels to the reference spatial frequency spectruminformation. In an embodiment, the spatial frequency generation circuit3614 includes one or more data structures 424 having at least one ofreference erythrocyte spatial frequency spectrum information, referencemalaria-infected erythrocyte spatial frequency spectrum information, orreference hemozoin spatial frequency spectrum information. In anembodiment, the spatial frequency generation circuit 3614 is furtherconfigured to partition the spatial frequency spectrum of the at leastfirst subset of pixels into one or more information subsets using atleast one of a Clustering protocol or a Learning protocol. In anembodiment, the spatial frequency generation circuit 3614 further isconfigured to partition the spatial frequency spectrum of the at leastfirst subset of pixels into one or information subsets using at leastone of a Fuzzy C-Means Clustering protocol, a Graph-Theoretic protocol,a Hierarchical Clustering protocol, a K-Means Clustering protocol, aLocality-Sensitive Hashing protocol, a Mixture of Gaussians protocol, aModel-Based Clustering protocol, a Cluster-Weighted Modeling protocol,an Expectations-Maximization protocol, a Principal Components Analysisprotocol, or a Partitioning protocol.

FIG. 37 shows an example of a method 3700. At 3710, the method 3700includes acquiring, using a detection circuit, one or more micrographsof a biological sample at one or more fields of view. At 3712, acquiringthe one or more micrographs of the biological sample includes capturingat least a first micrograph and a second micrographs based on a tilingprotocol. At 3714, acquiring the one or more micrographs of thebiological sample includes acquiring the one or more micrographs of thebiological sample at one or more focal depths.

At 3720, the method 3700 includes modifying a resolution of at least oneof the one or more micrographs and generating at least a first modifiedmicrograph. At 3722, modifying the micrograph resolution includesperforming a resizing operation on the micrograph. At 3724, modifyingthe micrograph resolution includes performing a pixel binning protocolon the micrograph. At 3726, modifying the micrograph resolution includesperforming an optimization protocol that resizes one or more pixels inthe micrograph based on an object detection protocol.

At 3730, the method 3700 includes generating a first filtered micrographby filtering the at least first modified micrograph based on a filteringprotocol. At 3732, generating the first filtered micrograph includesconvolving a filter kernel with one or more one or more pixie parametersassociated with the first modified micrograph to generate a filteredmicrograph. At 3734, generating the first filtered micrograph includesdetermining whether an intensity of one or more pixels of the at leastfirst modified micrograph satisfies a threshold value. At 3736,generating the first filtered micrograph includes convolving at least aportion of the micrograph with a filter kernel. At 3738, generating thefirst filtered micrograph includes convolving a filter kernel with theone or more pixle parameters and determining connected components of agraph for a plurality of pixels based on a result of the convolve. At3740, generating the first filtered micrograph includes convolving afilter kernel with the one or more pixle parameters and generating aprobability-value image associated with the first filtered micrograph.

At 3742, generating the first filtered micrograph includes partitioningthe at least one micrograph into the one or more pixel subsets using atleast one of a Clustering protocol or a Learning protocol. At 3744,generating the first filtered micrograph includes partitioning the atleast one micrograph into the one or more pixel subsets using at leastone of a Fuzzy C-Means Clustering protocol, a Graph-Theoretic protocol,a Hierarchical Clustering protocol, a K-Means Clustering protocol, aLocality-Sensitive Hashing protocol, a Mixture of Gaussians protocol, aModel-Based Clustering protocol, a Cluster-Weighted Modeling protocol,an Expectations-Maximization protocol, a Principal Components Analysisprotocol, or a Partitioning protocol.

At 3750, the method 3700 includes determining a disease state byidentifying objects of the biological sample in the filtered micrograph.At 3752, determining the disease state includes comparing theprobability-value to threshold criteria to indentify objects in themicrograph. At 3754, determining the disease state includes determiningconnected components of a graph representative of the object content inthe first modified micrograph based on the comparing of aprobability-value image to threshold criteria. At 3756, determining thedisease state includes determining a probability that the biologicalsample is infected with malaria. At 3758, determining the disease stateincludes determining a confidence level associated with a determinedprobability that the biological sample is infected with malaria. At3760, determining the disease state includes applying aDulmage-Mendelsohn decomposition protocol to at least a portion of themicrograph to identify connected components.

At 3770, the method 3700 includes acquiring one or more micrographs of abiological sample at one or more focal depths. At 3780, the method 3700includes causing the storage of the acquired one or more micrographs oneor more micrographs of the biological sample on to a physical datastructure 424.

EXAMPLE 2 Detecting Malaria in a Biological Sample

Image Acquisition

Referring to FIG. 38, In an embodiment, a malaria detection apparatus102 c takes micrographs from many fields of view on a biological sample(e.g., blood sample). In an embodiment, micrographs are streamed from asensor component 440 to one or more computing device 402 as they areacquired until a defined pattern of micrograph tiling over thebiological sample has been completed by a scanning stage. Eachmicrograph is stored to a storage device (e.g., a data structure 424)for archiving and processing for disease diagnosis while a sample stageis moves a sample to its next imaging target on a biological sample.

Automated Detection

In an embodiment, automated detection and counting of infected cells isaccomplished by a combination of statistical methods that quantify theprobability that an individual is infected and the confidence intervalon parasitemia (fraction of blood cells with a parasite).

Finding Significant Objects

In an embodiment, a micrograph is first adjusted in resolution bybinning pixels or applying another resize operation to optimize the sizeof each pixel in the micrograph for object detection. In an embodiment,objects infected with malaria are detected by measuring how bright theyare: infected cells appearing brighter than non-infected cells. In oneembodiment, a t-test filter is applied to the resized micrograph tomeasure the probability that a pixel is not any brighter than thebackground (the null hypothesis). A threshold is specified for the nullhypothesis, (e.g., 0.01) such that any pixel with a p-value less thanthe null hypothesis threshold is counted as being an objectsignificantly brighter than the background pixels. In an embodiment,background pixels are defined by a filter kernel as a region of somesize surrounding the pixel under test. This kernel is convolved over theentire micrograph, and the filter may be embodied as a nonlinear filter,a linear filter on nonlinear image intermediates, or a linear filter ofthe micrograph. In an embodiment, a t-test is implemented as a linearfilter on nonlinear image intermediates to increase the speed of thecomputation.

In an embodiment, pixels may be compared to the entire micrograph as thebackground distribution. However, there is a distinct advantage tofiltering with a kernel some fraction of the micrograph size: lateralbrightness adaptation is inherent to small kernels. The significancetest with such a kernel is insensitive to variations in illuminationintensity across the field of view and also ignores many objects largerthan the desired target.

Object Identification

In an embodiment, multiple pixels may be significant for one erythrocytein the micrograph and they need to be identified as a single object. Inan embodiment, objects (e.g., malaria-infected cells, etc.) areidentified by determining the connected components of the graph ofsignificant pixels. For example, a Dulmage-Mendelsohn decomposition ofthe adjacency matrix is determined to identify distinct groups ofsignificant pixels. In an embodiment, each connected component found islikely to be a malaria-infected cell (with a p-value returned by thet-test).

Spectral Screen for Specificity

To improve the specificity of diagnosis, in an embodiment, falsepositives are minimized by performing a spectral (e.g., spatialfrequency) analysis of the micrographs. For example, in an embodiment,for each significant object, multiple windows of different sized pixelregions are selected from the original (unresized) micrograph and fastFourier transform is determined to generate the spectral signature ofeach object. In an embodiment, the object spectrum is compared totemplates a stored library of spectra from previously-analyzed objects.In an embodiment, the library includes many samples of known infectedcells, autodetected infected cells, and a multitude of controls such asdust, scratches, fingerprints, healthy blood, out of focus, defectiveillumination, etc. The spectrum of each object is compared to one ormore of the reference spectra from the library using statistical teststo calculate the probability that the spectral signatures are the same.In an embodiment, thresholds of the null hypothesis (two spectra havethe same distribution) are applied to screen objects and select thosethat are consistent with the characteristics of an infected cell. In oneembodiment of the spectral screen, the 2D FFT is integrated in variouscoordinate systems to obtain the power spectra of the object in the x-,y-, radial-, and angular-directions. These power spectra are in factprobability density functions for the distribution of energy acrossspatial frequency in the micrograph. The Komolgorov-Smirnov test isapplied to calculate the null hypothesis for each power spectrumcompared to reference spectra in the library. In another embodiment,template matching is performed by cross-correlation of the 2D objectspectrum with 2D reference spectra in the library. Again, significancetests are applied to measure the probability that the object spectrummatches a spectrum from the library.

Diagnosis

In an embodiment, following object identification and spectral screens,only objects satisfying a threshold probability of being infected cellsare counted, along with the associated p-value for each object. In anembodiment, a diagnosis infected/not infected is generated along withthe calculated probability that the individual is in fact infected. Inan embodiment, a generate response includes reporting the number ofinfected cells, as a ratio of infected cells to total cells along withthe 95% confidence interval on that ratio.

Spectral Learning in the Template Library

In an embodiment, an object recognition circuit includes a library ofobjects with known identity under controlled conditions. In anembodiment, micrographs of infected cells are processed and the spectrasaved to the library to confirm the identity of significant objects. Inan embodiment, micrographs of non-infected samples are processed andsaved to the library for the purpose of rejecting false positives beforethey are counted in the diagnosis report. In an embodiment, spectralinformation from processed micrographs are stored in a data structurelibrary with its associated p-value. The variance and mean of libraryspectra are calculated with weights according to the probability that anobject spectrum belongs in the library category to which it was assigned(e.g., dust particle, etc.) by the template matching process.

Multidimensional Object Identification

In an embodiment, by using a stage that scans in 3 dimensions, with theaddition of z-axis for focus, more spatial information may be obtainedabout an object. For example, a very flat object can be distinguishedfrom a more spherical object of the same radius by moving the plan offocus and taking another micrograph. An additional embodiment of objectrecognition is to take 2 or more micrographs at different focal planesin the sample from the same field of view. In an embodiment,deconvolution of the micrograph stack is performed with or withoutknowledge of the point spread function to reconstruct the 3-dimentionalshape of the object. Again, template matching to a library is applied,but now in more dimensions. In an embodiment, approaches associated withmonochromatic micrographs can be applied to color micrographs byaddition of a dimension for optical wavelength. Spectral analysis canthen be performed in the spatial dimensions and the optical wavelengthdimension in combination.

In an embodiment, one or more components may be referred to herein as“configured to,” “configurable to,” “operable/operative to,”“adapted/adaptable,” “able to,” “conformable/conformed to,” etc. Suchterms (e.g., “configured to”) can generally encompass active-statecomponents and/or inactive-state components and/or standby-statecomponents, unless context requires otherwise.

The foregoing detailed description has set forth various embodiments ofthe devices and/or processes via the use of block diagrams, flowcharts,and/or examples. Insofar as such block diagrams, flowcharts, and/orexamples contain one or more functions and/or operations, it will beunderstood by the reader that each function and/or operation within suchblock diagrams, flowcharts, or examples can be implemented, individuallyand/or collectively, by a wide range of hardware, software, firmware, orvirtually any combination thereof. Further, the use of “Start,” “End” or“Stop” blocks in the block diagrams is not intended to indicate alimitation on the beginning or end of any functions in the diagram. Suchflowcharts or diagrams may be incorporated into other flowcharts ordiagrams where additional functions are performed before or after thefunctions shown in the diagrams of this application. In an embodiment,several portions of the subject matter described herein may beimplemented via Application Specific Integrated Circuits (ASICs), FieldProgrammable Gate Arrays (FPGAs), digital signal processors (DSPs), orother integrated formats. However, some aspects of the embodimentsdisclosed herein, in whole or in part, can be equivalently implementedin integrated circuits, as one or more computer programs running on oneor more computers (e.g., as one or more programs running on one or morecomputer systems), as one or more programs running on one or moreprocessors 404 (e.g., as one or more programs running on one or moremicroprocessors), as firmware, or as virtually any combination thereof,and that designing the circuitry and/or writing the code for thesoftware and or firmware would be well within the skill of one of skillin the art in light of this disclosure. In addition, the mechanisms ofthe subject matter described herein are capable of being distributed asa program product in a variety of forms, and that an illustrativeembodiment of the subject matter described herein applies regardless ofthe particular type of signal-bearing medium used to actually carry outthe distribution. Non-limiting examples of a signal-bearing mediuminclude the following: a recordable type medium such as a floppy disk, ahard disk drive, a Compact Disc (CD), a Digital Video Disk (DVD), adigital tape, a computer memory, etc.; and a transmission type mediumsuch as a digital and/or an analog communication medium (e.g., a fiberoptic cable, a waveguide, a wired communications link, a wirelesscommunication link (e.g., transmitter, receiver, transceiver,transmission logic, reception logic, etc.), etc.).

While particular aspects of the present subject matter described hereinhave been shown and described, it will be apparent to the reader that,based upon the teachings herein, changes and modifications may be madewithout departing from the subject matter described herein and itsbroader aspects and, therefore, the appended claims are to encompasswithin their scope all such changes and modifications as are within thetrue spirit and scope of the subject matter described herein. Ingeneral, terms used herein, and especially in the appended claims (e.g.,bodies of the appended claims) are generally intended as “open” terms(e.g., the term “including” should be interpreted as “including but notlimited to,” the term “having” should be interpreted as “having atleast,” the term “includes” should be interpreted as “includes but isnot limited to,” etc.). Further, if a specific number of an introducedclaim recitation is intended, such an intent will be explicitly recitedin the claim, and in the absence of such recitation no such intent ispresent. For example, as an aid to understanding, the following appendedclaims may contain usage of the introductory phrases “at least one” and“one or more” to introduce claim recitations. However, the use of suchphrases should not be construed to imply that the introduction of aclaim recitation by the indefinite articles “a” or “an” limits anyparticular claim containing such introduced claim recitation to claimscontaining only one such recitation, even when the same claim includesthe introductory phrases “one or more” or “at least one” and indefinitearticles such as “a” or “an” (e.g., “a” and/or “an” should typically beinterpreted to-mean “at least one” or “one or more”); the same holdstrue for the use of definite articles used to introduce claimrecitations. In addition, even if a specific number of an introducedclaim recitation is explicitly recited, such recitation should typicallybe interpreted to mean at least the recited number (e.g., the barerecitation of “two recitations,” without other modifiers, typicallymeans at least two recitations, or two or more recitations).Furthermore, in those instances where a convention analogous to “atleast one of A, B, and C, etc.” is used, in general such a constructionis intended in the sense of the convention (e.g., “a system having atleast one of A, B, and C” would include but not be limited to systemsthat have A alone, B alone, C alone, A and B together, A and C together,B and C together, and/or A, B, and C together, etc.). In those instanceswhere a convention analogous to “at least one of A, B, or C, etc.” isused, in general such a construction is intended in the sense of theconvention (e.g., “a system having at least one of A, B, or C” wouldinclude but not be limited to systems that have A alone, B alone, Calone, A and B together, A and C together, B and C together, and/or A,B, and C together, etc.). Typically a disjunctive word and/or phrasepresenting two or more alternative terms, whether in the description,claims, or drawings, should be understood to contemplate thepossibilities of including one of the terms, either of the terms, orboth terms unless context dictates otherwise. For example, the phrase “Aor B” will be typically understood to include the possibilities of “A”or “B” or “A and B.”

With respect to the appended claims, the operations recited thereingenerally may be performed in any order. Also, although variousoperational flows are presented in a sequence(s), it should beunderstood that the various operations may be performed in orders otherthan those that are illustrated, or may be performed concurrently.Examples of such alternate orderings may include overlapping,interleaved, interrupted, reordered, incremental, preparatory,supplemental, simultaneous, reverse, or other variant orderings, unlesscontext dictates otherwise. Furthermore, terms like “responsive to,”“related to,” or other past-tense adjectives are generally not intendedto exclude such variants, unless context dictates otherwise.

While various aspects and embodiments have been disclosed herein, otheraspects and embodiments are contemplated. The various aspects andembodiments disclosed herein are for purposes of illustration and arenot intended to be limiting, with the true scope and spirit beingindicated by the following claims.

1. A system, comprising: a detection circuit configured to acquire one or more micrographs of a biological sample at one or more fields of view; a resolution modification circuit configured to modify a pixel count of at least one micrograph and to generate at least a first modified micrograph; a filter-kernel generation circuit configured to generate a kernel for filtering a plurality of pixels forming the first modified micrograph based on a filtering characteristic, and to generate at least a first significance image representative of the at least one modified micrograph; and an object identification circuit configured to identify groups of pixels in the first significance image indicative of one or more objects imaged in the at least one micrograph, and to generate one or more connected components of a graph representative of groups of pixels indicative of the one or more objects imaged in the at least one micrograph.
 2. The system of claim 1, further comprising: a circuit configured to compare the generated one or more connected components of the graph to reference object information stored in one or more data structures, and to generate a response based on the comparison of the generated one or more connected components of the graph to the reference object information.
 3. The system of claim 2, wherein the circuit configured to compare the generated one or more connected components of the graph includes one or more data structures having reference object information stored thereon, the reference object information including at least one of erythrocyte graph information, malaria-infected erythrocyte graph information, or hemozoin graph information.
 4. The system of claim 2, wherein the circuit configured to compare the generated one or more connected components of the graph includes a circuit configured to generate a response including at least one of object identification information, a disease state, a parasitemia level, a erythrocyte count, a ratio of malaria-infected erythrocytes to total erythrocyte present in the at least one micrograph, or probability and confidence level information associated with an identified object.
 5. The system of claim 1, further comprising: a spatial frequency generation circuit configured to determine a spatial frequency spectrum of at least a first subset of pixels of the at least one micrograph, compare the spatial frequency spectrum of the first subset of pixels to reference spatial frequency spectrum information, and generate a response based on the comparison of the spatial frequency spectrum of the first subset of pixels to the reference spatial frequency spectrum information.
 6. The system of claim 5, wherein the spatial frequency generation circuit includes one or more data structures having at least one of reference erythrocyte spatial frequency spectrum information, reference malaria-infected erythrocyte spatial frequency spectrum information, or reference hemozoin spatial frequency spectrum information.
 7. The method of claim 14, wherein the spatial frequency generation circuit is further configured to partition the spatial frequency spectrum of the at least first subset of pixels into one or more information subsets using at least one of a Clustering protocol or a Learning protocol.
 8. The method of claim 14, wherein the spatial frequency generation circuit further configured to partition the spatial frequency spectrum of the at least first subset of pixels into one or information subsets using at least one of a Fuzzy C-Means Clustering protocol, a Graph-Theoretic protocol, a Hierarchical Clustering protocol, a K-Means Clustering protocol, a Locality-Sensitive Hashing protocol, a Mixture of Gaussians protocol, a Model-Based Clustering protocol, a Cluster-Weighted Modeling protocol, an Expectations-Maximization protocol, a Principal Components Analysis protocol, or a Partitioning protocol.
 9. The system of claim 1, wherein the object identification circuit includes a circuit configured to identify groups of pixels in the first significance image indicative of at least one of a hemozoin nanoparticle, a malaria-infected erythrocyte, or a non-infected erythrocyte in the at least one micrograph.
 10. The system according to claim 1, wherein the detection circuit includes one or more detectors configured to acquire one or more micrographs of a biological sample at one or more fields of view and at one or more focal depths.
 11. The system according to claim 1, wherein the resolution modification circuit includes one or more computing devices configured to modify a micrograph pixel resolution.
 12. The system according to claim 1, wherein the resolution modification circuit includes at least one computing device, and one or more data structures operable to generate and store a threshold comparison value, and to generate and store a kernel for filtering a plurality of pixels forming a micrograph based on the threshold comparison value.
 13. The system of claim 1, wherein the object identification circuit is configure to determine a probability that the biological sample is infected with malaria, and to determine a confidence level associated with the determined probability that the biological sample is infected with malaria.
 14. A method, comprising: acquiring, using a detection circuit, one or more micrographs of a biological sample at one or more fields of view; modifying a resolution of at least one of the one or more micrographs and generating at least a first modified micrograph; generating a first filtered micrograph by filtering the at least first modified micrograph based on a filtering protocol; and determining a disease state by identifying objects of the biological sample in the filtered micrograph.
 15. The method of claim 14, wherein acquiring the one or more micrographs of the biological sample includes capturing at least a first micrograph and a second micrographs based on a tiling protocol.
 16. The method of claim 14, wherein acquiring the one or more micrographs of the biological sample includes acquiring the one or more micrographs of the biological sample at one or more focal depths.
 17. The method of claim 14, wherein modifying the micrograph resolution includes performing a resizing operation on the micrograph.
 18. The method of claim 14, wherein modifying the micrograph resolution includes performing a pixel binning protocol on the micrograph.
 19. The method of claim 14, wherein modifying the micrograph resolution includes performing an optimization protocol that resizes one or more pixels in the micrograph based on an object detection protocol.
 20. The method of claim 14, wherein generating the first filtered micrograph includes convolving a filter kernel with one or more one or more pixie parameters associated with the first modified micrograph to generate a filtered micrograph.
 21. The method of claim 14, wherein generating the first filtered micrograph includes determining whether an intensity of one or more pixels of the at least first modified micrograph satisfies a threshold value.
 22. The method of claim 14, wherein generating the first filtered micrograph convolving at least a portion of the micrograph with a filter kernel.
 23. The method of claim 14, wherein generating the first filtered micrograph includes convolving a filter kernel with the one or more pixie parameters and determining connected components of a graph for a plurality of pixels based on a result of the convolve.
 24. The method of claim 14, wherein generating the first filtered micrograph includes convolving a filter kernel with the one or more pixie parameters and generating a probability-value image associated with the first filtered micrograph.
 25. The method of claim 24, wherein determining the disease state includes comparing the probability-value to threshold criteria to indentify objects in the micrograph.
 26. The method of claim 24, wherein determining the disease state includes determining connected components of a graph representative of the object content in the first modified micrograph based on the comparing of a probability-value image to threshold criteria.
 27. The method of claim 14, wherein determining the disease state includes determining a probability that the biological sample is infected with malaria.
 28. The method of claim 14, wherein determining the disease state includes determining a confidence level associated with a determined probability that the biological sample is infected with malaria.
 29. The method of claim 14, wherein determining the disease state includes applying a Dulmage-Mendelsohn decomposition protocol to at least a portion of the micrograph to identify connected components.
 30. The method of claim 14, wherein generating the first filtered micrograph includes partitioning the at least one micrograph into the one or more pixel subsets using at least one of a Clustering protocol or a Learning protocol.
 31. The method of claim 14, wherein generating the first filtered micrograph includes partitioning the at least one micrograph into the one or more pixel subsets using at least one of a Fuzzy C-Means Clustering protocol, a Graph-Theoretic protocol, a Hierarchical Clustering protocol, a K-Means Clustering protocol, a Locality-Sensitive Hashing protocol, a Mixture of Gaussians protocol, a Model-Based Clustering protocol, a Cluster-Weighted Modeling protocol, an Expectations-Maximization protocol, a Principal Components Analysis protocol, or a Partitioning protocol.
 32. The method of claim 14, further comprising: acquiring one or more micrographs of a biological sample at one or more focal depths.
 33. The method of claim 14, further comprising: causing the storage of the acquired one or more micrographs one or more micrographs of the biological sample on to a physical data structure. 